{
  "task": "expert_brief",
  "policy_label": "trained-cos",
  "use_rag": false,
  "success": true,
  "steps": 14,
  "terminal_score": 0.683,
  "cumulative_reward": 0.443,
  "step_rewards": [
    0.08,
    0.08,
    0.08,
    -0.05,
    -0.05,
    -0.05,
    -0.05,
    -0.05,
    -0.05,
    0.02,
    -0.05,
    -0.05,
    -0.05,
    0.633
  ],
  "trace": [
    {
      "step": 1,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": 0.08,
      "done": false,
      "consulted_experts": [
        "analyst"
      ]
    },
    {
      "step": 2,
      "action": {
        "action_type": "ask",
        "expert_id": "hr"
      },
      "reward": 0.08,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr"
      ]
    },
    {
      "step": 3,
      "action": {
        "action_type": "ask",
        "expert_id": "finance"
      },
      "reward": 0.08,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 4,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 5,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 6,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 7,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 8,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 9,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 10,
      "action": {
        "action_type": "summarize"
      },
      "reward": 0.02,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 11,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 12,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 13,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": -0.05,
      "done": false,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    },
    {
      "step": 14,
      "action": {
        "action_type": "ask",
        "expert_id": "analyst"
      },
      "reward": 0.633,
      "done": true,
      "consulted_experts": [
        "analyst",
        "hr",
        "finance"
      ]
    }
  ],
  "error": null,
  "final_instruction": "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.",
  "task_difficulty": "hard",
  "max_steps": 14,
  "consulted_experts": [
    "analyst",
    "hr",
    "finance"
  ],
  "current_brief": {
    "summary": "Cleaned 11 raw rows into 10 trusted rows. Top category is Electronics and total revenue is 248400.00. Finance projects next quarter at 41880.00 and marks performance as ahead plan.",
    "metrics": {
      "duplicates_removed": 1,
      "imputed_prices": 1,
      "data_quality_score": 1.0,
      "total_revenue": 248400.0,
      "avg_order_value": 24840.0,
      "top_category": "Electronics",
      "top_category_revenue": 224600.0,
      "projection_next_quarter": 41880.0,
      "confidence_band": 84151.78,
      "variance_abs": 160400.0,
      "variance_pct": 182.27,
      "variance_flag": "ahead",
      "break_even_units": 16.0,
      "break_even_revenue": 32000.0
    },
    "recommendations": [],
    "hr_memo": "Hello CFO and strategy leads,\n\nThank you for moving quickly on this update.\nHere is the latest business update for Full expert stack \u2014 data, finance, market strategy, comms.\n- Removed 1 duplicate rows and imputed 1 missing prices.\n- Data quality score is 1.00 with 0 invalid date rows.\n- Next-quarter revenue projection is 41880.00 with +/- 84151.78 band.\n- Variance versus plan is 160400.00 (182.27%).\n\nPlease review the actions above and reply with any blockers today.\nBest,\nHR Operations",
    "consulted_experts": [
      "analyst",
      "hr",
      "finance"
    ]
  },
  "expert_reports": {
    "analyst": {
      "expert_id": "analyst",
      "title": "Data Analyst Report",
      "summary": "Cleaned 11 raw rows into 10 trusted rows. Top category is Electronics and total revenue is 248400.00.",
      "metrics": {
        "duplicates_removed": 1,
        "imputed_prices": 1,
        "data_quality_score": 1.0,
        "total_revenue": 248400.0,
        "avg_order_value": 24840.0,
        "top_category": "Electronics",
        "top_category_revenue": 224600.0
      },
      "bullet_points": [
        "Removed 1 duplicate rows and imputed 1 missing prices.",
        "Data quality score is 1.00 with 0 invalid date rows.",
        "Electronics leads revenue at 224600.00."
      ],
      "issues": [],
      "citations": [
        "Electronics",
        "Home",
        "Fashion"
      ],
      "memory_citations": [],
      "memory_snippets": [],
      "memo": null,
      "score": null
    },
    "hr": {
      "expert_id": "hr",
      "title": "HR / Communications Memo",
      "summary": "Drafted the internal memo and scored it on structure, professional tone, and audience relevance.",
      "metrics": {
        "memo_structure_score": 0.9333,
        "memo_tone_score": 0.39,
        "audience_reference": 1.0,
        "memo_score": 0.6955
      },
      "bullet_points": [
        "Memo addressed to CFO and strategy leads.",
        "Structure score 0.933, tone score 0.390.",
        "Blended score uses 45% structure, 45% tone, 10% audience bonus."
      ],
      "issues": [
        "hr:weak_professional_tone"
      ],
      "citations": [],
      "memory_citations": [],
      "memory_snippets": [],
      "memo": "Hello CFO and strategy leads,\n\nThank you for moving quickly on this update.\nHere is the latest business update for Full expert stack \u2014 data, finance, market strategy, comms.\n- Removed 1 duplicate rows and imputed 1 missing prices.\n- Data quality score is 1.00 with 0 invalid date rows.\n- Next-quarter revenue projection is 41880.00 with +/- 84151.78 band.\n- Variance versus plan is 160400.00 (182.27%).\n\nPlease review the actions above and reply with any blockers today.\nBest,\nHR Operations",
      "score": 0.6955
    },
    "finance": {
      "expert_id": "finance",
      "title": "Finance Forecast",
      "summary": "Finance projects next quarter at 41880.00 and marks performance as ahead plan.",
      "metrics": {
        "projection_next_quarter": 41880.0,
        "confidence_band": 84151.78,
        "variance_abs": 160400.0,
        "variance_pct": 182.27,
        "variance_flag": "ahead",
        "break_even_units": 16.0,
        "break_even_revenue": 32000.0
      },
      "bullet_points": [
        "Next-quarter revenue projection is 41880.00 with +/- 84151.78 band.",
        "Variance versus plan is 160400.00 (182.27%).",
        "Break-even sits at 16.00 units."
      ],
      "issues": [],
      "citations": [
        "2024-03",
        "2024-04",
        "2024-05"
      ],
      "memory_citations": [],
      "memory_snippets": [],
      "memo": null,
      "score": null
    }
  }
}