{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 0\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=0/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=[]; missing=['analyst', 'finance', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":0,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: none\n- still missing: analyst, finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for easy_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 0\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=0/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=[]; missing=['analyst', 'finance', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":0,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: none\n- still missing: analyst, finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for easy_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 0\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=0/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=[]; missing=['analyst', 'finance', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":0,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: none\n- still missing: analyst, finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for easy_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 1\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=1/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst']; missing=['finance', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":1,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst\n- still missing: finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for easy_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst'] | missing=['finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 1\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=1/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst']; missing=['finance', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":1,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst\n- still missing: finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for easy_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst'] | missing=['finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 1\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=1/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst']; missing=['finance', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":1,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst\n- still missing: finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for easy_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst'] | missing=['finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 2\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=2/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":2,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for easy_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 2\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=2/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":2,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for easy_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 2\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=2/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":2,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for easy_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 3\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=3/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":3,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 3\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=3/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":3,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 3\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=3/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":3,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 4\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=4/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":4,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 4\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=4/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":4,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 4\nmax_steps: 8\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=4/8; rag=False; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":4,\"max_steps\":8,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 0\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=0/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=[]; missing=['analyst', 'finance', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":0,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: none\n- still missing: analyst, finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for easy_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 0\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=0/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=[]; missing=['analyst', 'finance', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":0,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: none\n- still missing: analyst, finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for easy_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 0\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=0/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=[]; missing=['analyst', 'finance', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":0,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: none\n- still missing: analyst, finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for easy_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 1\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=1/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst']; missing=['finance', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":1,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst\n- still missing: finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for easy_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst'] | missing=['finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 1\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=1/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst']; missing=['finance', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":1,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst\n- still missing: finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for easy_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst'] | missing=['finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 1\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=1/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst']; missing=['finance', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":1,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst\n- still missing: finance, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for easy_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst'] | missing=['finance', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 2\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=2/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":2,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for easy_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 2\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=2/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":2,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for easy_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 2\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=2/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":2,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for easy_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 3\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=3/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":3,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 3\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=3/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":3,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 3\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=3/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":3,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 4\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=4/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":4,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 4\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=4/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":4,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: easy_brief\ntask_difficulty: easy\nstep_count: 4\nmax_steps: 8\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'hr']\nconsulted_experts: ['analyst', 'finance', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Is our raw sales file trustworthy, what's next quarter's revenue looking like, and send the team a one-paragraph update."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=easy_brief; difficulty=easy; step=4/8; rag=True; required=['analyst', 'finance', 'hr']; consulted=['analyst', 'finance', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"easy_brief\",\"difficulty\":\"easy\",\"step\":4,\"max_steps\":8,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: easy_brief\n- required experts: analyst, finance, hr\n- already consulted: analyst, finance, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for easy_brief. Consulted experts are ['analyst', 'finance', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=easy_brief | required=['analyst', 'finance', 'hr'] | consulted=['analyst', 'finance', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 0\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=0/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":0,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for medium_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 0\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=0/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":0,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for medium_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 0\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=0/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":0,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for medium_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 1\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=1/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":1,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for medium_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 1\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=1/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":1,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for medium_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 1\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=1/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":1,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for medium_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 2\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=2/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":2,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for medium_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 2\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=2/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":2,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for medium_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 2\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=2/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":2,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for medium_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 3\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=3/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":3,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 3\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=3/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":3,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 3\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=3/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":3,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 4\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=4/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":4,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 4\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=4/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":4,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 4\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=4/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":4,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 5\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=5/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":5,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 5 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 5\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=5/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":5,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 5 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 5\nmax_steps: 10\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=5/10; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":5,\"max_steps\":10,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 5 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 0\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=0/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":0,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for medium_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 0\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=0/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":0,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for medium_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 0\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=0/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":0,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for medium_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 1\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=1/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":1,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for medium_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 1\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=1/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":1,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for medium_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 1\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=1/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":1,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for medium_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 2\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=2/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":2,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for medium_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 2\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=2/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":2,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for medium_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 2\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=2/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":2,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for medium_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 3\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=3/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":3,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 3\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=3/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":3,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 3\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=3/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":3,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 4\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=4/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":4,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 4\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=4/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":4,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 4\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=4/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":4,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 5\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=5/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":5,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 5 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 5\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=5/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":5,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 5 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: medium_brief\ntask_difficulty: medium\nstep_count: 5\nmax_steps: 10\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Which category drove Q3 growth, what is the Q4 forecast plus variance versus plan, what should we do about it, and send the leads a heads-up."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=medium_brief; difficulty=medium; step=5/10; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"medium_brief\",\"difficulty\":\"medium\",\"step\":5,\"max_steps\":10,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: medium_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 5 for medium_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=medium_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=0/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for hard_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=0/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for hard_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=0/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for hard_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=1/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for hard_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=1/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for hard_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=1/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for hard_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=2/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for hard_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=2/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for hard_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=2/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for hard_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=3/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=3/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=3/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=4/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=4/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=4/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=5/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 5 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=5/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 5 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 12\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=5/12; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":12,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 5 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=0/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for hard_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=0/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for hard_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=0/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for hard_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=1/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for hard_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=1/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for hard_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=1/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for hard_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=2/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for hard_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=2/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for hard_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=2/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for hard_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=3/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=3/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=3/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=4/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=4/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=4/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=5/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 5 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=5/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 5 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: hard_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 12\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Prepare a board-ready revenue summary with risk flags, Q4 forecast with scenarios, strategic recommendation, and a CFO-facing memo."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=hard_brief; difficulty=hard; step=5/12; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"hard_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":12,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: hard_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 5 for hard_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=hard_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=0/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for expert_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=0/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for expert_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=0/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for expert_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=1/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for expert_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=1/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for expert_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=1/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for expert_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=2/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for expert_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=2/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for expert_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=2/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for expert_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=3/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=3/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=3/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=4/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=4/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=4/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=5/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=5/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 14\nrag_enabled: False\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=5/14; rag=False; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":14,\"rag_enabled\":false,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is False."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=0/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 0 for expert_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=0/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 0 for expert_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 0\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: []\nmissing_required_experts: ['analyst', 'finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 0.0\nrecent_issues: ['No experts consulted yet.']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=0/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=[]; missing=['analyst', 'finance', 'strategy', 'hr']; brief_ready=False; dq=0.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":0,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[],\"missing_required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":0.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: none\n- still missing: analyst, finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 0 for expert_brief. Consulted experts are []. The next priority is one of the missing experts: ['analyst', 'finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=[] | missing=['analyst', 'finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"analyst\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=1/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 1 for expert_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=1/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 1 for expert_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 1\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst']\nmissing_required_experts: ['finance', 'strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['analyst:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=1/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst']; missing=['finance', 'strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":1,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\"],\"missing_required_experts\":[\"finance\",\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst\n- still missing: finance, strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 1 for expert_brief. Consulted experts are ['analyst']. The next priority is one of the missing experts: ['finance', 'strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst'] | missing=['finance', 'strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"finance\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=2/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 2 for expert_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=2/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 2 for expert_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 2\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance']\nmissing_required_experts: ['strategy', 'hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['finance:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=2/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance']; missing=['strategy', 'hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":2,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\"],\"missing_required_experts\":[\"strategy\",\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance\n- still missing: strategy, hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 2 for expert_brief. Consulted experts are ['analyst', 'finance']. The next priority is one of the missing experts: ['strategy', 'hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance'] | missing=['strategy', 'hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"strategy\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=3/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 3 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=3/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 3 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 3\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy']\nmissing_required_experts: ['hr']\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['strategy:ok']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=3/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy']; missing=['hr']; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":3,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\"],\"missing_required_experts\":[\"hr\"],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy\n- still missing: hr\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 3 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy']. The next priority is one of the missing experts: ['hr']. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy'] | missing=['hr'] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"consult\",\"expert_id\":\"hr\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=4/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 4 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=4/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 4 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 4\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: False\ndata_quality_score: 1.0\nrecent_issues: ['hr:weak_professional_tone']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=4/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=False; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":4,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":false,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: False\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 4 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. All required experts are consulted, but the brief is not summarized yet. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=False | action?"}, {"role": "assistant", "content": "{\"action_type\":\"summarize\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=5/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.\n\nSchema: {\"action_type\": one of [\"consult\", \"ask\", \"summarize\", \"submit\", \"noop\"], \"expert_id\": one of [\"analyst\", \"finance\", \"hr\", \"strategy\"] or null, \"sub_question_id\": string or null, \"notes\": string or null}.\nRules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=5/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "task_name: expert_brief\ntask_difficulty: hard\nstep_count: 5\nmax_steps: 14\nrag_enabled: True\navailable_experts: ['analyst', 'finance', 'hr', 'strategy']\nrequired_experts: ['analyst', 'finance', 'strategy', 'hr']\nconsulted_experts: ['analyst', 'finance', 'strategy', 'hr']\nmissing_required_experts: []\ncurrent_brief_present: True\ndata_quality_score: 1.0\nrecent_issues: ['brief_composed']\ninstruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Task=expert_brief; difficulty=hard; step=5/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "{\"task\":\"expert_brief\",\"difficulty\":\"hard\",\"step\":5,\"max_steps\":14,\"rag_enabled\":true,\"required_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"consulted_experts\":[\"analyst\",\"finance\",\"strategy\",\"hr\"],\"missing_required_experts\":[],\"brief_ready\":true,\"data_quality_score\":1.0}"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "Decision checklist:\n- task: expert_brief\n- required experts: analyst, finance, strategy, hr\n- already consulted: analyst, finance, strategy, hr\n- still missing: none\n- brief composed: True\n- choose the single next action"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True."}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}
{"messages": [{"role": "system", "content": "You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation."}, {"role": "user", "content": "state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?"}, {"role": "assistant", "content": "{\"action_type\":\"submit\"}"}]}