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Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_0e1de2b9700436a0/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": "m6",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m6_0e1de2b9700436a0",
+    "api_calls": 0,
+    "input_tokens": 14937,
+    "cached_input_tokens": 12032,
+    "output_tokens": 273,
+    "total_tokens": 15210,
+    "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": 7678.43,
+    "sql_execution_elapsed_ms_total": 5.78,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_0e1de2b9700436a0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_0e1de2b9700436a0/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": "2026-05-19T15:31:43.185160+00:00",
+  "ended_at": "2026-05-19T15:31:50.863627+00:00",
+  "elapsed_ms": 7678.43,
+  "prompt_metrics": {
+    "chars": 10408,
+    "bytes_utf8": 10408,
+    "lines": 312,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 769,
+    "bytes_utf8": 769,
+    "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": 407,
+      "bytes_utf8": 407,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14937,
+      "cached_input_tokens": 12032,
+      "output_tokens": 273,
+      "reasoning_output_tokens": 167
+    }
+  },
+  "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_b/m6/artifacts/v2q_m6_0e1de2b9700436a0/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,312 @@
+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: m6
+- dataset_name: Online Shoppers Purchasing Intention Dataset
+- table_name: m6
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 17 feature columns and target `VisitorType`.
+- task_type: classification
+- target_column: VisitorType
+- main_row_count: 12330
+- important_fields:
+- Administrative: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Administrative.
+- Administrative_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Administrative Duration.
+- Informational: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Informational.
+- Informational_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Informational Duration.
+- ProductRelated: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated.
+- ProductRelated_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated Duration.
+- BounceRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for BounceRates.
+- ExitRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ExitRates.
+- PageValues: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for PageValues.
+- SpecialDay: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for SpecialDay.
+- Month: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Month.
+- OperatingSystems: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for OperatingSystems.
+- Browser: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Browser.
+- Region: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Region.
+- TrafficType: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for TrafficType.
+- VisitorType: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for VisitorType.
+- Weekend: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Weekend.
+- Revenue: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Revenue.
+- useful_field_combinations: [['Administrative', 'Informational', 'VisitorType'], ['Administrative', 'Administrative', 'VisitorType'], ['Administrative', 'Administrative_Duration', 'VisitorType']]
+- fields_requiring_caution: ['VisitorType', 'Administrative_Duration', 'Informational_Duration', 'ProductRelated']
+- source_url: https://archive.ics.uci.edu/dataset/468/online+shoppers+purchasing+intention+dataset
+
+SQLite schema snapshot:
+{
+  "table_name": "m6",
+  "quoted_table_name": "\"m6\"",
+  "row_count": 12330,
+  "columns": [
+    {
+      "name": "Administrative",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Administrative_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "BounceRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ExitRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PageValues",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "SpecialDay",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "OperatingSystems",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Browser",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Region",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "TrafficType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "VisitorType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Weekend",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Revenue",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "1",
+      "Browser": "1",
+      "Region": "1",
+      "TrafficType": "1",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "64",
+      "BounceRates": "0",
+      "ExitRates": "0.1",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "2",
+      "Browser": "2",
+      "Region": "1",
+      "TrafficType": "2",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "4",
+      "Browser": "1",
+      "Region": "9",
+      "TrafficType": "3",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "2.666666667",
+      "BounceRates": "0.05",
+      "ExitRates": "0.14",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "2",
+      "Region": "2",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "10",
+      "ProductRelated_Duration": "627.5",
+      "BounceRates": "0.02",
+      "ExitRates": "0.05",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "3",
+      "Region": "1",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "TRUE",
+      "Revenue": "FALSE"
+    }
+  ]
+}
+
+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": "m6",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=VisitorType, measure_col=PageValues.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "VisitorType",
+    "measure_col": "PageValues",
+    "top_k": 18,
+    "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": 0.0,
+    "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}, 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_b/m6/artifacts/v2q_m6_0e1de2b9700436a0/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40dd-44dd-7fb0-a670-8767a74de26c"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"VisitorType\\\", SUM(CAST(\\\"PageValues\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m6\\\"\\nGROUP BY \\\"VisitorType\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the planned Grouped Numeric Sum template with group_col=\\\"VisitorType\\\" and measure_col=\\\"PageValues\\\". CAST to REAL is applied because the schema stores numeric-looking fields as TEXT in SQLite.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14937,"cached_input_tokens":12032,"output_tokens":273,"reasoning_output_tokens":167}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_0e1de2b9700436a0/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"VisitorType\", SUM(CAST(\"PageValues\" AS REAL)) AS \"total_measure\"\nFROM \"m6\"\nGROUP BY \"VisitorType\"\nORDER BY \"total_measure\" DESC;","notes":"Used the planned Grouped Numeric Sum template with group_col=\"VisitorType\" and measure_col=\"PageValues\". CAST to REAL is applied because the schema stores numeric-looking fields as TEXT in SQLite."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_37c10ebffa066e2e/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10580, "bytes_utf8": 10580, "lines": 312, "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": 1734, "bytes_utf8": 1734, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14973, "cached_input_tokens": 13696, "output_tokens": 1102, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_37c10ebffa066e2e/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": "m6",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m6_37c10ebffa066e2e",
+    "api_calls": 0,
+    "input_tokens": 14973,
+    "cached_input_tokens": 13696,
+    "output_tokens": 1102,
+    "total_tokens": 16075,
+    "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": 19320.84,
+    "sql_execution_elapsed_ms_total": 64.19,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_37c10ebffa066e2e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_37c10ebffa066e2e/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": "2026-05-19T15:59:02.880080+00:00",
+  "ended_at": "2026-05-19T15:59:22.200947+00:00",
+  "elapsed_ms": 19320.84,
+  "prompt_metrics": {
+    "chars": 10580,
+    "bytes_utf8": 10580,
+    "lines": 312,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2319,
+    "bytes_utf8": 2319,
+    "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": 1734,
+      "bytes_utf8": 1734,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 14973,
+      "cached_input_tokens": 13696,
+      "output_tokens": 1102,
+      "reasoning_output_tokens": 516
+    }
+  },
+  "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_b/m6/artifacts/v2q_m6_37c10ebffa066e2e/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,312 @@
+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: m6
+- dataset_name: Online Shoppers Purchasing Intention Dataset
+- table_name: m6
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 17 feature columns and target `VisitorType`.
+- task_type: classification
+- target_column: VisitorType
+- main_row_count: 12330
+- important_fields:
+- Administrative: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Administrative.
+- Administrative_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Administrative Duration.
+- Informational: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Informational.
+- Informational_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Informational Duration.
+- ProductRelated: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated.
+- ProductRelated_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated Duration.
+- BounceRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for BounceRates.
+- ExitRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ExitRates.
+- PageValues: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for PageValues.
+- SpecialDay: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for SpecialDay.
+- Month: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Month.
+- OperatingSystems: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for OperatingSystems.
+- Browser: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Browser.
+- Region: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Region.
+- TrafficType: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for TrafficType.
+- VisitorType: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for VisitorType.
+- Weekend: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Weekend.
+- Revenue: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Revenue.
+- useful_field_combinations: [['Administrative', 'Informational', 'VisitorType'], ['Administrative', 'Administrative', 'VisitorType'], ['Administrative', 'Administrative_Duration', 'VisitorType']]
+- fields_requiring_caution: ['VisitorType', 'Administrative_Duration', 'Informational_Duration', 'ProductRelated']
+- source_url: https://archive.ics.uci.edu/dataset/468/online+shoppers+purchasing+intention+dataset
+
+SQLite schema snapshot:
+{
+  "table_name": "m6",
+  "quoted_table_name": "\"m6\"",
+  "row_count": 12330,
+  "columns": [
+    {
+      "name": "Administrative",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Administrative_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "BounceRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ExitRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PageValues",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "SpecialDay",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "OperatingSystems",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Browser",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Region",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "TrafficType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "VisitorType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Weekend",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Revenue",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "1",
+      "Browser": "1",
+      "Region": "1",
+      "TrafficType": "1",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "64",
+      "BounceRates": "0",
+      "ExitRates": "0.1",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "2",
+      "Browser": "2",
+      "Region": "1",
+      "TrafficType": "2",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "4",
+      "Browser": "1",
+      "Region": "9",
+      "TrafficType": "3",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "2.666666667",
+      "BounceRates": "0.05",
+      "ExitRates": "0.14",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "2",
+      "Region": "2",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "10",
+      "ProductRelated_Duration": "627.5",
+      "BounceRates": "0.02",
+      "ExitRates": "0.05",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "3",
+      "Region": "1",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "TRUE",
+      "Revenue": "FALSE"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "required_roles": [
+      "group_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m6",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=Browser, measure_col=SpecialDay.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "Browser",
+    "measure_col": "SpecialDay",
+    "top_k": 18,
+    "top_n": 5,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "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": 0.0,
+    "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       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_37c10ebffa066e2e/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f6-49f5-7053-ae77-71bf4248480b"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"Browser\\\",\\n    CAST(\\\"SpecialDay\\\" AS REAL) AS \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"Browser\\\"\\n      ORDER BY CAST(\\\"SpecialDay\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"Browser\\\") AS \\\"cnt\\\"\\n  FROM \\\"m6\\\"\\n  WHERE \\\"Browser\\\" IS NOT NULL\\n    AND \\\"SpecialDay\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT\\n    \\\"Browser\\\",\\n    (1.0 + (\\\"cnt\\\" - 1) * 0.95) AS \\\"pos\\\",\\n    CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN (1.0 + (\\\"cnt\\\" - 1) * 0.95) = CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER)\\n        THEN CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER)\\n      ELSE CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER) + 1\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ordered\\\"\\n  GROUP BY \\\"Browser\\\", \\\"cnt\\\"\\n)\\nSELECT\\n  p.\\\"Browser\\\",\\n  CASE\\n    WHEN p.\\\"lower_rn\\\" = p.\\\"upper_rn\\\" THEN MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN o.\\\"measure\\\" END)\\n    ELSE\\n      MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN o.\\\"measure\\\" END) +\\n      (p.\\\"pos\\\" - p.\\\"lower_rn\\\") * (\\n        MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN o.\\\"measure\\\" END) -\\n        MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN o.\\\"measure\\\" END)\\n      )\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"positions\\\" AS p\\nJOIN \\\"ordered\\\" AS o\\n  ON o.\\\"Browser\\\" = p.\\\"Browser\\\"\\nGROUP BY p.\\\"Browser\\\", p.\\\"pos\\\", p.\\\"lower_rn\\\", p.\\\"upper_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"Emulated the 0.95 percentile in SQLite using window functions and linear interpolation because SQLite does not support PERCENTILE_CONT. Cast \\\"SpecialDay\\\" to REAL since the schema stores it as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":14973,"cached_input_tokens":13696,"output_tokens":1102,"reasoning_output_tokens":516}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_37c10ebffa066e2e/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"Browser\",\n    CAST(\"SpecialDay\" AS REAL) AS \"measure\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"Browser\"\n      ORDER BY CAST(\"SpecialDay\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (PARTITION BY \"Browser\") AS \"cnt\"\n  FROM \"m6\"\n  WHERE \"Browser\" IS NOT NULL\n    AND \"SpecialDay\" IS NOT NULL\n),\n\"positions\" AS (\n  SELECT\n    \"Browser\",\n    (1.0 + (\"cnt\" - 1) * 0.95) AS \"pos\",\n    CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER) AS \"lower_rn\",\n    CASE\n      WHEN (1.0 + (\"cnt\" - 1) * 0.95) = CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER)\n        THEN CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER)\n      ELSE CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER) + 1\n    END AS \"upper_rn\"\n  FROM \"ordered\"\n  GROUP BY \"Browser\", \"cnt\"\n)\nSELECT\n  p.\"Browser\",\n  CASE\n    WHEN p.\"lower_rn\" = p.\"upper_rn\" THEN MAX(CASE WHEN o.\"rn\" = p.\"lower_rn\" THEN o.\"measure\" END)\n    ELSE\n      MAX(CASE WHEN o.\"rn\" = p.\"lower_rn\" THEN o.\"measure\" END) +\n      (p.\"pos\" - p.\"lower_rn\") * (\n        MAX(CASE WHEN o.\"rn\" = p.\"upper_rn\" THEN o.\"measure\" END) -\n        MAX(CASE WHEN o.\"rn\" = p.\"lower_rn\" THEN o.\"measure\" END)\n      )\n  END AS \"percentile_measure\"\nFROM \"positions\" AS p\nJOIN \"ordered\" AS o\n  ON o.\"Browser\" = p.\"Browser\"\nGROUP BY p.\"Browser\", p.\"pos\", p.\"lower_rn\", p.\"upper_rn\"\nORDER BY \"percentile_measure\" DESC;","notes":"Emulated the 0.95 percentile in SQLite using window functions and linear interpolation because SQLite does not support PERCENTILE_CONT. Cast \"SpecialDay\" to REAL since the schema stores it as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_6fc4bcadf7999e4d/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10989, "bytes_utf8": 10989, "lines": 312, "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": 648, "bytes_utf8": 648, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15077, "cached_input_tokens": 12288, "output_tokens": 453, "reasoning_output_tokens": 290}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_6fc4bcadf7999e4d/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": "m6",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m6_6fc4bcadf7999e4d",
+    "api_calls": 0,
+    "input_tokens": 15077,
+    "cached_input_tokens": 12288,
+    "output_tokens": 453,
+    "total_tokens": 15530,
+    "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": 10598.98,
+    "sql_execution_elapsed_ms_total": 7.24,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_6fc4bcadf7999e4d/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_6fc4bcadf7999e4d/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": "2026-05-19T15:46:16.203605+00:00",
+  "ended_at": "2026-05-19T15:46:26.802610+00:00",
+  "elapsed_ms": 10598.98,
+  "prompt_metrics": {
+    "chars": 10989,
+    "bytes_utf8": 10989,
+    "lines": 312,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1015,
+    "bytes_utf8": 1015,
+    "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": 648,
+      "bytes_utf8": 648,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 15077,
+      "cached_input_tokens": 12288,
+      "output_tokens": 453,
+      "reasoning_output_tokens": 290
+    }
+  },
+  "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_b/m6/artifacts/v2q_m6_6fc4bcadf7999e4d/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,312 @@
+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: m6
+- dataset_name: Online Shoppers Purchasing Intention Dataset
+- table_name: m6
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 17 feature columns and target `VisitorType`.
+- task_type: classification
+- target_column: VisitorType
+- main_row_count: 12330
+- important_fields:
+- Administrative: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Administrative.
+- Administrative_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Administrative Duration.
+- Informational: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Informational.
+- Informational_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for Informational Duration.
+- ProductRelated: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated.
+- ProductRelated_Duration: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ProductRelated Duration.
+- BounceRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for BounceRates.
+- ExitRates: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ExitRates.
+- PageValues: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for PageValues.
+- SpecialDay: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for SpecialDay.
+- Month: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Month.
+- OperatingSystems: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for OperatingSystems.
+- Browser: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Browser.
+- Region: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for Region.
+- TrafficType: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for TrafficType.
+- VisitorType: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for VisitorType.
+- Weekend: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Weekend.
+- Revenue: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for Revenue.
+- useful_field_combinations: [['Administrative', 'Informational', 'VisitorType'], ['Administrative', 'Administrative', 'VisitorType'], ['Administrative', 'Administrative_Duration', 'VisitorType']]
+- fields_requiring_caution: ['VisitorType', 'Administrative_Duration', 'Informational_Duration', 'ProductRelated']
+- source_url: https://archive.ics.uci.edu/dataset/468/online+shoppers+purchasing+intention+dataset
+
+SQLite schema snapshot:
+{
+  "table_name": "m6",
+  "quoted_table_name": "\"m6\"",
+  "row_count": 12330,
+  "columns": [
+    {
+      "name": "Administrative",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Administrative_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Informational_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ProductRelated_Duration",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "BounceRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ExitRates",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PageValues",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "SpecialDay",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Month",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "OperatingSystems",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Browser",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Region",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "TrafficType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "VisitorType",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Weekend",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "Revenue",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "1",
+      "Browser": "1",
+      "Region": "1",
+      "TrafficType": "1",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "64",
+      "BounceRates": "0",
+      "ExitRates": "0.1",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "2",
+      "Browser": "2",
+      "Region": "1",
+      "TrafficType": "2",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "1",
+      "ProductRelated_Duration": "0",
+      "BounceRates": "0.2",
+      "ExitRates": "0.2",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "4",
+      "Browser": "1",
+      "Region": "9",
+      "TrafficType": "3",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "2",
+      "ProductRelated_Duration": "2.666666667",
+      "BounceRates": "0.05",
+      "ExitRates": "0.14",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "2",
+      "Region": "2",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "FALSE",
+      "Revenue": "FALSE"
+    },
+    {
+      "Administrative": "0",
+      "Administrative_Duration": "0",
+      "Informational": "0",
+      "Informational_Duration": "0",
+      "ProductRelated": "10",
+      "ProductRelated_Duration": "627.5",
+      "BounceRates": "0.02",
+      "ExitRates": "0.05",
+      "PageValues": "0",
+      "SpecialDay": "0",
+      "Month": "Feb",
+      "OperatingSystems": "3",
+      "Browser": "3",
+      "Region": "1",
+      "TrafficType": "4",
+      "VisitorType": "Returning_Visitor",
+      "Weekend": "TRUE",
+      "Revenue": "FALSE"
+    }
+  ]
+}
+
+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": "m6",
+  "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=Weekend, measure_col=ProductRelated_Duration.",
+  "planned_template_id": "tpl_tpch_relative_total_threshold",
+  "bindings": {
+    "group_col": "Weekend",
+    "measure_col": "ProductRelated_Duration",
+    "top_k": 15,
+    "top_n": 7,
+    "num_tiles": 10,
+    "percentile_value": 0.95,
+    "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": 1059.697712,
+    "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_b/m6/artifacts/v2q_m6_6fc4bcadf7999e4d/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40ea-971d-7b53-aa80-d5dc15ed3889"}
+{"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 \\\"Weekend\\\", SUM(CAST(\\\"ProductRelated_Duration\\\" AS REAL)) AS group_value\\n    FROM \\\"m6\\\"\\n    GROUP BY \\\"Weekend\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"Weekend\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Used the required Relative-to-Total Extreme Threshold template with group_col=\\\"Weekend\\\" and measure_col=\\\"ProductRelated_Duration\\\", casting the measure from TEXT to REAL for SQLite aggregation.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":15077,"cached_input_tokens":12288,"output_tokens":453,"reasoning_output_tokens":290}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m6/artifacts/v2q_m6_6fc4bcadf7999e4d/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"Weekend\", SUM(CAST(\"ProductRelated_Duration\" AS REAL)) AS group_value\n    FROM \"m6\"\n    GROUP BY \"Weekend\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"Weekend\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;","notes":"Used the required Relative-to-Total Extreme Threshold template with group_col=\"Weekend\" and measure_col=\"ProductRelated_Duration\", casting the measure from TEXT to REAL for SQLite aggregation."}