Add files using upload-large-folder tool

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16349, "bytes_utf8": 16349, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 415, "bytes_utf8": 415, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16685, "cached_input_tokens": 12032, "output_tokens": 339, "reasoning_output_tokens": 229}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/session_summary.json

@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_084bdbd6ba92f76a",
+    "api_calls": 0,
+    "input_tokens": 16685,
+    "cached_input_tokens": 12032,
+    "output_tokens": 339,
+    "total_tokens": 17024,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 10073.23,
+    "sql_execution_elapsed_ms_total": 1.15,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:29:51.935586+00:00",
+  "ended_at": "2026-05-19T15:30:02.008835+00:00",
+  "elapsed_ms": 10073.23,
+  "prompt_metrics": {
+    "chars": 16349,
+    "bytes_utf8": 16349,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 781,
+    "bytes_utf8": 781,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 415,
+      "bytes_utf8": 415,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16685,
+      "cached_input_tokens": 12032,
+      "output_tokens": 339,
+      "reasoning_output_tokens": 229
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "primary_family": "subgroup_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=Location_Type, measure_col=Productivity_Score.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "Location_Type",
+    "measure_col": "Productivity_Score",
+    "top_k": 19,
+    "top_n": 4,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.05,
+    "baseline_multiplier": 1.75,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 4,
+    "measure_threshold": 94.8,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40db-923b-7b70-974f-2e2c6f4fae52"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"Location_Type\\\", SUM(CAST(\\\"Productivity_Score\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m1\\\"\\nGROUP BY \\\"Location_Type\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied the provided Grouped Numeric Sum template with group_col=\\\"Location_Type\\\" and measure_col=\\\"Productivity_Score\\\". Cast \\\"Productivity_Score\\\" to REAL because the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16685,"cached_input_tokens":12032,"output_tokens":339,"reasoning_output_tokens":229}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_084bdbd6ba92f76a/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"Location_Type\", SUM(CAST(\"Productivity_Score\" AS REAL)) AS \"total_measure\"\nFROM \"m1\"\nGROUP BY \"Location_Type\"\nORDER BY \"total_measure\" DESC;","notes":"Applied the provided Grouped Numeric Sum template with group_col=\"Location_Type\" and measure_col=\"Productivity_Score\". Cast \"Productivity_Score\" to REAL because the schema stores it as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16899, "bytes_utf8": 16899, "lines": 456, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 632, "bytes_utf8": 632, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16827, "cached_input_tokens": 15744, "output_tokens": 421, "reasoning_output_tokens": 246}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/session_summary.json

@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_0978a623dc7f6b02",
+    "api_calls": 0,
+    "input_tokens": 16827,
+    "cached_input_tokens": 15744,
+    "output_tokens": 421,
+    "total_tokens": 17248,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 11770.09,
+    "sql_execution_elapsed_ms_total": 1.57,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:47:01.625725+00:00",
+  "ended_at": "2026-05-19T15:47:13.395852+00:00",
+  "elapsed_ms": 11770.09,
+  "prompt_metrics": {
+    "chars": 16899,
+    "bytes_utf8": 16899,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1003,
+    "bytes_utf8": 1003,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 632,
+      "bytes_utf8": 632,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16827,
+      "cached_input_tokens": 15744,
+      "output_tokens": 421,
+      "reasoning_output_tokens": 246
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Location_Type, measure_col=WFH_Days_Per_Week.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Location_Type",
+    "measure_col": "WFH_Days_Per_Week",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40eb-4870-7e40-ae2d-b7ae088e12db"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"Location_Type\\\", SUM(CAST(\\\"WFH_Days_Per_Week\\\" AS REAL)) AS group_value\\n    FROM \\\"m1\\\"\\n    GROUP BY \\\"Location_Type\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"Location_Type\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the planned template with group_col=\\\"Location_Type\\\" and measure_col=\\\"WFH_Days_Per_Week\\\". Cast \\\"WFH_Days_Per_Week\\\" from TEXT to REAL for SQLite aggregation.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16827,"cached_input_tokens":15744,"output_tokens":421,"reasoning_output_tokens":246}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_0978a623dc7f6b02/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"Location_Type\", SUM(CAST(\"WFH_Days_Per_Week\" AS REAL)) AS group_value\n    FROM \"m1\"\n    GROUP BY \"Location_Type\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"Location_Type\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;","notes":"Applied the planned template with group_col=\"Location_Type\" and measure_col=\"WFH_Days_Per_Week\". Cast \"WFH_Days_Per_Week\" from TEXT to REAL for SQLite aggregation."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16496, "bytes_utf8": 16496, "lines": 454, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 584, "bytes_utf8": 584, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16734, "cached_input_tokens": 15744, "output_tokens": 518, "reasoning_output_tokens": 362}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/session_summary.json

@@ -0,0 +1,25 @@
+{
+  "engine": "v2-cli:codex",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "ai_cli_calls": 1,
+  "usage_summary": {
+    "dataset_id": "m1",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m1_10b98eafb0959930",
+    "api_calls": 0,
+    "input_tokens": 16734,
+    "cached_input_tokens": 15744,
+    "output_tokens": 518,
+    "total_tokens": 17252,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 1,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 18236.41,
+    "sql_execution_elapsed_ms_total": 2.56,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,45 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T15:46:43.382613+00:00",
+  "ended_at": "2026-05-19T15:47:01.619062+00:00",
+  "elapsed_ms": 18236.41,
+  "prompt_metrics": {
+    "chars": 16496,
+    "bytes_utf8": 16496,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1293,
+    "bytes_utf8": 1293,
+    "lines": 5,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 584,
+      "bytes_utf8": 584,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 16734,
+      "cached_input_tokens": 15744,
+      "output_tokens": 518,
+      "reasoning_output_tokens": 362
+    }
+  },
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "primary_family": "tail_rarity_structure",
+    "portability": "partial",
+    "sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Stress_Level.",
+  "planned_template_id": "tpl_m4_quantile_tail_slice",
+  "bindings": {
+    "measure_col": "Stress_Level",
+    "top_k": 13,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 7.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40eb-01c1-7722-96a3-7b2eb771fbee"}
+{"type":"turn.started"}
+{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17369. Please try again in 521ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT\\n        CAST(\\\"Stress_Level\\\" AS REAL) AS \\\"Stress_Level\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"Stress_Level\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n    FROM \\\"m1\\\"\\n)\\nSELECT \\\"Stress_Level\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"Stress_Level\\\" DESC;\",\"notes\":\"Used the requested Quantile Tail Slice template with measure_col bound to \\\"Stress_Level\\\" and num_tiles=10. Cast \\\"Stress_Level\\\" from TEXT to REAL so the tail bucket and descending order are numeric, not lexicographic.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":16734,"cached_input_tokens":15744,"output_tokens":518,"reasoning_output_tokens":362}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_10b98eafb0959930/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n    SELECT\n        CAST(\"Stress_Level\" AS REAL) AS \"Stress_Level\",\n        NTILE(10) OVER (ORDER BY CAST(\"Stress_Level\" AS REAL) DESC) AS \"tail_bucket\"\n    FROM \"m1\"\n)\nSELECT \"Stress_Level\"\nFROM buckets\nWHERE \"tail_bucket\" = 1\nORDER BY \"Stress_Level\" DESC;","notes":"Used the requested Quantile Tail Slice template with measure_col bound to \"Stress_Level\" and num_tiles=10. Cast \"Stress_Level\" from TEXT to REAL so the tail bucket and descending order are numeric, not lexicographic."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:22.712207+00:00",
+  "ended_at": "2026-05-19T16:06:26.989445+00:00",
+  "elapsed_ms": 4277.21,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16245,
+    "bytes_utf8": 16245,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:06:27.992388+00:00",
+  "ended_at": "2026-05-19T16:06:30.860455+00:00",
+  "elapsed_ms": 2868.02,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16245,
+    "bytes_utf8": 16245,
+    "lines": 454,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Age.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Age",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,454 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "required_roles": [
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=Age.",
+  "planned_template_id": "tpl_threshold_rarity_cdf",
+  "bindings": {
+    "measure_col": "Age",
+    "top_k": 12,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 41.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-000d-7260-87ee-eb6638054cb8"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-000d-7260-87ee-eb6638054cb8"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-14a2-7b60-a523-f2e3f5160dc1"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_11b6612b4f30770f/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fd-14a2-7b60-a523-f2e3f5160dc1"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16783, "bytes_utf8": 16783, "lines": 458, "estimated_tokens": null}}
+{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 686, "bytes_utf8": 686, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16810, "cached_input_tokens": 15744, "output_tokens": 704, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_125f5b1eba679c5e/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"Team_Collaboration_Frequency\",\n  \"Quality_Score\",\n  SUM(CAST(\"Years_Experience\" AS REAL)) AS total_measure,\n  SUM(CAST(\"Years_Experience\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"Years_Experience\" AS REAL))) OVER (PARTITION BY \"Team_Collaboration_Frequency\") AS share_within_group\nFROM \"m1\"\nGROUP BY \"Team_Collaboration_Frequency\", \"Quality_Score\"\nORDER BY share_within_group DESC;","notes":"Used the fixed template bindings exactly: group_col=Team_Collaboration_Frequency, item_col=Quality_Score, measure_col=Years_Experience. Cast Years_Experience to REAL because the SQLite schema stores it as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:04:10.842074+00:00",
+  "ended_at": "2026-05-19T16:04:15.271782+00:00",
+  "elapsed_ms": 4429.68,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16660,
+    "bytes_utf8": 16660,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:04:16.273658+00:00",
+  "ended_at": "2026-05-19T16:04:19.394508+00:00",
+  "elapsed_ms": 3120.82,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16660,
+    "bytes_utf8": 16660,
+    "lines": 459,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Survey_Date, condition_col=Internet_Speed_Category.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Survey_Date",
+    "condition_col": "Internet_Speed_Category",
+    "condition_value": "Very Fast (100+ Mbps)",
+    "positive_value": "Very Fast (100+ Mbps)",
+    "negative_value": "Fast (50-100 Mbps)",
+    "top_k": 10,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,459 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "required_roles": [
+      "group_col",
+      "condition_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=Survey_Date, condition_col=Internet_Speed_Category.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "Survey_Date",
+    "condition_col": "Internet_Speed_Category",
+    "condition_value": "Very Fast (100+ Mbps)",
+    "positive_value": "Very Fast (100+ Mbps)",
+    "negative_value": "Fast (50-100 Mbps)",
+    "top_k": 10,
+    "top_n": 3,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 4.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fa-fcf1-7880-8df7-f2dd6fa927bd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fa-fcf1-7880-8df7-f2dd6fa927bd"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-123c-74f3-bd28-6fd76a646857"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_139036e5df54854f/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fb-123c-74f3-bd28-6fd76a646857"}
+{"type":"turn.started"}
+{"type":"error","message":"Quota exceeded. Check your plan and billing details."}
+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_1.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 1,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:01.104498+00:00",
+  "ended_at": "2026-05-19T16:11:04.442167+00:00",
+  "elapsed_ms": 3337.64,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16424,
+    "bytes_utf8": 16424,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_1.txt",
+  "response_path": "cli/sql_response_attempt_1.txt",
+  "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_1.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_attempt_2.metadata.json

@@ -0,0 +1,43 @@
+{
+  "attempt": 2,
+  "phase": "sql_generation",
+  "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
+  "started_at": "2026-05-19T16:11:05.443960+00:00",
+  "ended_at": "2026-05-19T16:11:08.370180+00:00",
+  "elapsed_ms": 2926.19,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 16424,
+    "bytes_utf8": 16424,
+    "lines": 456,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 281,
+    "bytes_utf8": 281,
+    "lines": 4,
+    "estimated_tokens": null
+  },
+  "stderr_metrics": {
+    "chars": 0,
+    "bytes_utf8": 0,
+    "lines": 0,
+    "estimated_tokens": null
+  },
+  "parsed_output": {
+    "format": "jsonl_events",
+    "text_metrics": {
+      "chars": 280,
+      "bytes_utf8": 280,
+      "lines": 4,
+      "estimated_tokens": null
+    },
+    "usage": {}
+  },
+  "status": "failed",
+  "error": "AI CLI command failed with exit code 1: ",
+  "prompt_path": "cli/sql_prompt_attempt_2.txt",
+  "response_path": "cli/sql_response_attempt_2.txt",
+  "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
+  "stderr_path": "cli/sql_stderr_attempt_2.txt"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Has_Children, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Life_Balance",
+    "top_k": 14,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,456 @@
+You are generating one SQLite SELECT query for a single-table SQL QA task.
+Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
+Rules:
+- Use only the provided table and columns.
+- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
+- Prefer the planned template and bound roles when provided.
+- Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
+- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
+- Quote identifiers with double quotes.
+- Return no markdown and no extra prose.
+
+Dataset context:
+Dataset context for SQL QA:
+- dataset_id: m1
+- dataset_name: Remote Worker Productivity
+- table_name: m1
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one employee survey/assessment record in a remote-work context.
+- task_type: classification
+- target_column: Response_Quality
+- main_row_count: 1500
+- important_fields:
+- Employee_ID: role=identifier, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Employee identifier.
+- Age: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Employee age in years.
+- Years_Experience: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Years of professional experience.
+- WFH_Days_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of work-from-home days per week.
+- Gender: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Self-reported gender category.
+- Education_Level: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Highest education category.
+- Marital_Status: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Marital status category.
+- Has_Children: role=feature, type=categorical_binary. tags=['condition_candidate', 'subgroup_candidate'] desc=Whether the employee has children.
+- Location_Type: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Residential location type.
+- Department: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Work department/function.
+- Job_Level: role=feature, type=categorical_ordinal. ordered=['Junior', 'Mid-Level', 'Senior', 'Lead', 'Manager', 'Director'] tags=['condition_candidate', 'subgroup_candidate'] desc=Job seniority level.
+- Company_Size: role=feature, type=categorical_ordinal. ordered=['Startup (1-50)', 'Small (51-200)', 'Medium (201-1000)', 'Large (1001-5000)', 'Enterprise (5000+)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Employer size bracket.
+- Industry: role=feature, type=categorical_nominal. tags=['condition_candidate', 'subgroup_candidate'] desc=Industry sector.
+- Home_Office_Quality: role=feature, type=categorical_ordinal. ordered=['Poor', 'Average', 'Good', 'Excellent'] tags=['condition_candidate', 'subgroup_candidate'] desc=Self-rated home office quality.
+- Internet_Speed_Category: role=feature, type=categorical_ordinal. ordered=['Slow (<25 Mbps)', 'Moderate (25-50 Mbps)', 'Fast (50-100 Mbps)', 'Very Fast (100+ Mbps)'] tags=['condition_candidate', 'subgroup_candidate'] desc=Internet speed category at home office.
+- Work_Hours_Per_Week: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Average work hours per week.
+- Manager_Support_Level: role=feature, type=categorical_ordinal. ordered=['Very Low', 'Low', 'Moderate', 'High', 'Very High'] tags=['condition_candidate', 'subgroup_candidate'] desc=Perceived manager support level.
+- Team_Collaboration_Frequency: role=feature, type=categorical_ordinal. ordered=['Monthly', 'Bi-weekly', 'Weekly', 'Few times per week', 'Daily'] tags=['condition_candidate', 'subgroup_candidate'] desc=Frequency of team collaboration.
+- Productivity_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Productivity score.
+- Task_Completion_Rate: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Task completion rate score.
+- Quality_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Work quality score.
+- Innovation_Score: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Innovation score.
+- Efficiency_Rating: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Efficiency rating score.
+- Meetings_Per_Week: role=feature, type=numeric_discrete. tags=['condition_candidate', 'measure'] desc=Number of meetings per week.
+- Commute_Time_Minutes: role=feature, type=numeric. tags=['condition_candidate', 'measure'] desc=Typical commute time in minutes.
+- Job_Satisfaction: role=feature, type=numeric_score. tags=['condition_candidate', 'measure', 'response_candidate'] desc=Job satisfaction score.
+- Stress_Level: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Stress level (scaled score).
+- Work_Life_Balance: role=feature, type=numeric_ordinal_scale. tags=['condition_candidate', 'measure'] desc=Work-life balance score (scaled).
+- Survey_Date: role=feature, type=date. tags=['time_candidate', 'condition_candidate'] desc=Survey date.
+- Response_Quality: role=target, type=categorical_ordinal_target. ordered=['Low', 'Medium', 'High'] tags=['target_candidate'] desc=Response quality class label.
+- useful_field_combinations: [['Department', 'Job_Level', 'Response_Quality'], ['Manager_Support_Level', 'Team_Collaboration_Frequency', 'Response_Quality'], ['WFH_Days_Per_Week', 'Home_Office_Quality', 'Productivity_Score']]
+- fields_requiring_caution: ['Employee_ID', 'Productivity_Score', 'Task_Completion_Rate', 'Quality_Score', 'Efficiency_Rating', 'Job_Satisfaction']
+- source_url: https://huggingface.co/datasets/nprak26/remote-worker-productivity
+
+SQLite schema snapshot:
+{
+  "table_name": "m1",
+  "quoted_table_name": "\"m1\"",
+  "row_count": 1500,
+  "columns": [
+    {
+      "name": "Employee_ID",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Age",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Years_Experience",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "WFH_Days_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Gender",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Education_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Marital_Status",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Has_Children",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Location_Type",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Department",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Company_Size",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Industry",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Home_Office_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Internet_Speed_Category",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Hours_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Manager_Support_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Team_Collaboration_Frequency",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Productivity_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Task_Completion_Rate",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Quality_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Innovation_Score",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Efficiency_Rating",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Meetings_Per_Week",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Commute_Time_Minutes",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Job_Satisfaction",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Stress_Level",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Work_Life_Balance",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Survey_Date",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Response_Quality",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Employee_ID": "EMP0001",
+      "Age": "39",
+      "Years_Experience": "10",
+      "WFH_Days_Per_Week": "2",
+      "Gender": "Female",
+      "Education_Level": "Associate Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Product",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Large (1001-5000)",
+      "Industry": "Finance",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "41",
+      "Manager_Support_Level": "Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "52.2",
+      "Task_Completion_Rate": "56.6",
+      "Quality_Score": "58.1",
+      "Innovation_Score": "52.1",
+      "Efficiency_Rating": "72.1",
+      "Meetings_Per_Week": "4",
+      "Commute_Time_Minutes": "48",
+      "Job_Satisfaction": "55.9",
+      "Stress_Level": "6",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-04-05",
+      "Response_Quality": "Medium"
+    },
+    {
+      "Employee_ID": "EMP0002",
+      "Age": "33",
+      "Years_Experience": "4",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Female",
+      "Education_Level": "Master Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "No",
+      "Location_Type": "Urban",
+      "Department": "Customer Success",
+      "Job_Level": "Senior",
+      "Company_Size": "Startup (1-50)",
+      "Industry": "Education",
+      "Home_Office_Quality": "Good",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "52",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Monthly",
+      "Productivity_Score": "81.5",
+      "Task_Completion_Rate": "70.8",
+      "Quality_Score": "93.3",
+      "Innovation_Score": "77.9",
+      "Efficiency_Rating": "89.5",
+      "Meetings_Per_Week": "12",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "96.1",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "8",
+      "Survey_Date": "2024-01-29",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0003",
+      "Age": "40",
+      "Years_Experience": "3",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "PhD",
+      "Marital_Status": "Single",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Operations",
+      "Job_Level": "Mid-Level",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Fast (50-100 Mbps)",
+      "Work_Hours_Per_Week": "43",
+      "Manager_Support_Level": "Moderate",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "82.2",
+      "Task_Completion_Rate": "81.9",
+      "Quality_Score": "84.7",
+      "Innovation_Score": "63.2",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "15",
+      "Commute_Time_Minutes": "24",
+      "Job_Satisfaction": "90.4",
+      "Stress_Level": "5",
+      "Work_Life_Balance": "6",
+      "Survey_Date": "2024-01-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0004",
+      "Age": "48",
+      "Years_Experience": "14",
+      "WFH_Days_Per_Week": "3",
+      "Gender": "Male",
+      "Education_Level": "Bachelor Degree",
+      "Marital_Status": "Married",
+      "Has_Children": "Yes",
+      "Location_Type": "Urban",
+      "Department": "Finance",
+      "Job_Level": "Manager",
+      "Company_Size": "Medium (201-1000)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Excellent",
+      "Internet_Speed_Category": "Very Fast (100+ Mbps)",
+      "Work_Hours_Per_Week": "45",
+      "Manager_Support_Level": "High",
+      "Team_Collaboration_Frequency": "Daily",
+      "Productivity_Score": "75.6",
+      "Task_Completion_Rate": "70.2",
+      "Quality_Score": "67.8",
+      "Innovation_Score": "82.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "8",
+      "Commute_Time_Minutes": "8",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "10",
+      "Work_Life_Balance": "5",
+      "Survey_Date": "2024-04-18",
+      "Response_Quality": "High"
+    },
+    {
+      "Employee_ID": "EMP0005",
+      "Age": "32",
+      "Years_Experience": "6",
+      "WFH_Days_Per_Week": "5",
+      "Gender": "Male",
+      "Education_Level": "High School",
+      "Marital_Status": "Divorced",
+      "Has_Children": "Yes",
+      "Location_Type": "Rural",
+      "Department": "Engineering",
+      "Job_Level": "Senior",
+      "Company_Size": "Small (51-200)",
+      "Industry": "Technology",
+      "Home_Office_Quality": "Average",
+      "Internet_Speed_Category": "Moderate (25-50 Mbps)",
+      "Work_Hours_Per_Week": "42",
+      "Manager_Support_Level": "Very Low",
+      "Team_Collaboration_Frequency": "Few times per week",
+      "Productivity_Score": "98.0",
+      "Task_Completion_Rate": "98.2",
+      "Quality_Score": "86.4",
+      "Innovation_Score": "67.5",
+      "Efficiency_Rating": "95.0",
+      "Meetings_Per_Week": "10",
+      "Commute_Time_Minutes": "0",
+      "Job_Satisfaction": "100.0",
+      "Stress_Level": "3",
+      "Work_Life_Balance": "4",
+      "Survey_Date": "2024-02-19",
+      "Response_Quality": "High"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m1",
+  "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=Has_Children, measure_col=Work_Life_Balance.",
+  "planned_template_id": "tpl_m4_window_partition_avg",
+  "bindings": {
+    "group_col": "Has_Children",
+    "measure_col": "Work_Life_Balance",
+    "top_k": 14,
+    "top_n": 6,
+    "num_tiles": 10,
+    "percentile_value": 0.9,
+    "z_threshold": 2.0,
+    "fraction_threshold": 0.1,
+    "baseline_multiplier": 1.5,
+    "baseline_fraction": 0.1,
+    "min_group_size": 5,
+    "min_support": 5,
+    "measure_threshold": 8.0,
+    "time_grain": "month",
+    "lookback_rows": 3,
+    "current_period_start": "'2024-01-01'",
+    "current_period_end": "'2024-04-01'",
+    "previous_period_start": "'2023-10-01'",
+    "previous_period_end": "'2024-01-01'",
+    "drift_ratio_threshold": 0.8
+  },
+  "can_vary": [],
+  "must_fix": [],
+  "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.raw.txt

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Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_1.txt

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+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/m1/artifacts/v2q_m1_1401ef72a5912839/cli/sql_response_attempt_2.raw.txt

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+{"type":"turn.started"}
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+{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}