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Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=V, condition_col=PE.
+Result preview: [{"V": 79.05, "condition_rate": 0.25}, {"V": 76.2, "condition_rate": 0.07692307692307693}, {"V": 74.9, "condition_rate": 0.07692307692307693}, {"V": 70.4, "condition_rate": 0.0625}, {"V": 67.25, "condition_rate": 0.05}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/generated_sql.sql

@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n20
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n20_020bced1422a6427
+-- problem_id: v2p_n20_13a24488157fca0e
+-- realization_mode: agent
+-- source_kind: agent
+SELECT CAST("V" AS REAL) AS "V",
+       AVG(CASE WHEN CAST("PE" AS REAL) = 434.01 THEN 1 ELSE 0 END) AS "condition_rate"
+FROM "n20"
+GROUP BY CAST("V" AS REAL)
+ORDER BY "condition_rate" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT CAST(\"V\" AS REAL) AS \"V\",\n       AVG(CASE WHEN CAST(\"PE\" AS REAL) = 434.01 THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"n20\"\nGROUP BY CAST(\"V\" AS REAL)\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT CAST(\\\"V\\\" AS REAL) AS \\\"V\\\",\\n       AVG(CASE WHEN CAST(\\\"PE\\\" AS REAL) = 434.01 THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n20\\\"\\nGROUP BY CAST(\\\"V\\\" AS REAL)\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"V\", \"condition_rate\"], \"rows\": [{\"V\": 79.05, \"condition_rate\": 0.25}, {\"V\": 76.2, \"condition_rate\": 0.07692307692307693}, {\"V\": 74.9, \"condition_rate\": 0.07692307692307693}, {\"V\": 70.4, \"condition_rate\": 0.0625}, {\"V\": 67.25, \"condition_rate\": 0.05}, {\"V\": 67.45, \"condition_rate\": 0.047619047619047616}, {\"V\": 71.58, \"condition_rate\": 0.045454545454545456}, {\"V\": 71.32, \"condition_rate\": 0.03571428571428571}, {\"V\": 81.56, \"condition_rate\": 0.0}, {\"V\": 80.25, \"condition_rate\": 0.0}, {\"V\": 80.18, \"condition_rate\": 0.0}, {\"V\": 79.74, \"condition_rate\": 0.0}, {\"V\": 78.92, \"condition_rate\": 0.0}, {\"V\": 78.87, \"condition_rate\": 0.0}, {\"V\": 78.11, \"condition_rate\": 0.0}, {\"V\": 78.05, \"condition_rate\": 0.0}, {\"V\": 77.95, \"condition_rate\": 0.0}, {\"V\": 77.54, \"condition_rate\": 0.0}, {\"V\": 77.3, \"condition_rate\": 0.0}, {\"V\": 77.24, \"condition_rate\": 0.0}, {\"V\": 77.17, \"condition_rate\": 0.0}, {\"V\": 76.86, \"condition_rate\": 0.0}, {\"V\": 76.16, \"condition_rate\": 0.0}, {\"V\": 76.09, \"condition_rate\": 0.0}, {\"V\": 75.6, \"condition_rate\": 0.0}, {\"V\": 75.33, \"condition_rate\": 0.0}, {\"V\": 75.23, \"condition_rate\": 0.0}, {\"V\": 75.08, \"condition_rate\": 0.0}, {\"V\": 74.99, \"condition_rate\": 0.0}, {\"V\": 74.93, \"condition_rate\": 0.0}, {\"V\": 74.87, \"condition_rate\": 0.0}, {\"V\": 74.78, \"condition_rate\": 0.0}, {\"V\": 74.67, \"condition_rate\": 0.0}, {\"V\": 74.34, \"condition_rate\": 0.0}, {\"V\": 74.33, \"condition_rate\": 0.0}, {\"V\": 74.22, \"condition_rate\": 0.0}, {\"V\": 74.16, \"condition_rate\": 0.0}, {\"V\": 73.91, \"condition_rate\": 0.0}, {\"V\": 73.9, \"condition_rate\": 0.0}, {\"V\": 73.88, \"condition_rate\": 0.0}, {\"V\": 73.77, \"condition_rate\": 0.0}, {\"V\": 73.68, \"condition_rate\": 0.0}, {\"V\": 73.67, \"condition_rate\": 0.0}, {\"V\": 73.56, \"condition_rate\": 0.0}, {\"V\": 73.5, \"condition_rate\": 0.0}, {\"V\": 73.46, \"condition_rate\": 0.0}, {\"V\": 73.42, \"condition_rate\": 0.0}, {\"V\": 73.4, \"condition_rate\": 0.0}, {\"V\": 73.21, \"condition_rate\": 0.0}, {\"V\": 73.18, \"condition_rate\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.89}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/run_manifest.json

@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n20",
+  "started_at": "2026-05-19T15:59:23.550484+00:00",
+  "ended_at": "2026-05-19T15:59:36.908633+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n20_020bced1422a6427",
+    "problem_id": "v2p_n20_13a24488157fca0e",
+    "dataset_id": "n20",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=V, condition_col=PE.",
+    "bindings": {
+      "group_col": "V",
+      "condition_col": "PE",
+      "condition_value": "434.01",
+      "positive_value": "468.8",
+      "negative_value": "434.01",
+      "top_k": 16,
+      "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": 25.72,
+      "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
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=2/2",
+      "binding_index=96"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 1,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/sql/v2q_n20_020bced1422a6427.sql",
+  "usage_summary": {
+    "dataset_id": "n20",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n20_020bced1422a6427",
+    "api_calls": 0,
+    "input_tokens": 13585,
+    "cached_input_tokens": 12672,
+    "output_tokens": 611,
+    "total_tokens": 14196,
+    "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": 13346.27,
+    "sql_execution_elapsed_ms_total": 7.89,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:59:36.899272+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13346.27, "started_at": "2026-05-19T15:59:23.552147+00:00", "ended_at": "2026-05-19T15:59:36.898450+00:00", "prompt_metrics": {"chars": 4803, "bytes_utf8": 4803, "lines": 159, "estimated_tokens": null}, "response_metrics": {"chars": 483, "bytes_utf8": 483, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13585, "cached_input_tokens": 12672, "output_tokens": 611, "reasoning_output_tokens": 479}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT CAST(\\\"V\\\" AS REAL) AS \\\"V\\\",\\n       AVG(CASE WHEN CAST(\\\"PE\\\" AS REAL) = 434.01 THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n20\\\"\\nGROUP BY CAST(\\\"V\\\" AS REAL)\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the Grouped Condition Rate template with group_col=\\\"V\\\" and condition_col=\\\"PE\\\". Casts both TEXT-backed numeric columns to REAL so grouping and equality comparison follow numeric semantics in SQLite.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n20",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n20_020bced1422a6427",
+  "api_calls": 0,
+  "input_tokens": 13585,
+  "cached_input_tokens": 12672,
+  "output_tokens": 611,
+  "total_tokens": 14196,
+  "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": 13346.27,
+  "sql_execution_elapsed_ms_total": 7.89,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_020bced1422a6427/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/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": "2026-05-19T16:05:19.353771+00:00",
+  "ended_at": "2026-05-19T16:05:22.483343+00:00",
+  "elapsed_ms": 3129.55,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 4545,
+    "bytes_utf8": 4545,
+    "lines": 154,
+    "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/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/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": "2026-05-19T16:05:23.485423+00:00",
+  "ended_at": "2026-05-19T16:05:26.774167+00:00",
+  "elapsed_ms": 3288.7,
+  "returncode": 1,
+  "prompt_metrics": {
+    "chars": 4545,
+    "bytes_utf8": 4545,
+    "lines": 154,
+    "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/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,154 @@
+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: n20
+- dataset_name: Combined Cycle Power Plant
+- table_name: n20
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 4 feature columns and target `PE`.
+- task_type: regression
+- target_column: PE
+- main_row_count: 9568
+- important_fields:
+- AT: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AT.
+- V: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate', 'subgroup_candidate'] desc=Numeric field for V.
+- AP: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AP.
+- RH: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for RH.
+- PE: role=target, type=numeric_target. tags=['condition_candidate', 'target_candidate'] desc=Target field for PE.
+- useful_field_combinations: [['V', 'AT', 'PE'], ['AT', 'V', 'PE']]
+- fields_requiring_caution: ['PE', 'AT', 'V', 'AP']
+- source_url: https://archive.ics.uci.edu/dataset/294/combined+cycle+power+plant
+
+SQLite schema snapshot:
+{
+  "table_name": "n20",
+  "quoted_table_name": "\"n20\"",
+  "row_count": 9568,
+  "columns": [
+    {
+      "name": "AT",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "V",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "AP",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "RH",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PE",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "AT": "14.96",
+      "V": "41.76",
+      "AP": "1024.07",
+      "RH": "73.17",
+      "PE": "463.26"
+    },
+    {
+      "AT": "25.18",
+      "V": "62.96",
+      "AP": "1020.04",
+      "RH": "59.08",
+      "PE": "444.37"
+    },
+    {
+      "AT": "5.1100000000000003",
+      "V": "39.4",
+      "AP": "1012.16",
+      "RH": "92.14",
+      "PE": "488.56"
+    },
+    {
+      "AT": "20.86",
+      "V": "57.32",
+      "AP": "1010.24",
+      "RH": "76.64",
+      "PE": "446.48"
+    },
+    {
+      "AT": "10.82",
+      "V": "37.5",
+      "AP": "1009.23",
+      "RH": "96.62",
+      "PE": "473.9"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "n20",
+  "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=V.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "V",
+    "top_k": 11,
+    "top_n": 5,
+    "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": 1017.26,
+    "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\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/cli/sql_prompt_attempt_2.txt

@@ -0,0 +1,154 @@
+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: n20
+- dataset_name: Combined Cycle Power Plant
+- table_name: n20
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 4 feature columns and target `PE`.
+- task_type: regression
+- target_column: PE
+- main_row_count: 9568
+- important_fields:
+- AT: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AT.
+- V: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate', 'subgroup_candidate'] desc=Numeric field for V.
+- AP: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AP.
+- RH: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for RH.
+- PE: role=target, type=numeric_target. tags=['condition_candidate', 'target_candidate'] desc=Target field for PE.
+- useful_field_combinations: [['V', 'AT', 'PE'], ['AT', 'V', 'PE']]
+- fields_requiring_caution: ['PE', 'AT', 'V', 'AP']
+- source_url: https://archive.ics.uci.edu/dataset/294/combined+cycle+power+plant
+
+SQLite schema snapshot:
+{
+  "table_name": "n20",
+  "quoted_table_name": "\"n20\"",
+  "row_count": 9568,
+  "columns": [
+    {
+      "name": "AT",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "V",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "AP",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "RH",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PE",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "AT": "14.96",
+      "V": "41.76",
+      "AP": "1024.07",
+      "RH": "73.17",
+      "PE": "463.26"
+    },
+    {
+      "AT": "25.18",
+      "V": "62.96",
+      "AP": "1020.04",
+      "RH": "59.08",
+      "PE": "444.37"
+    },
+    {
+      "AT": "5.1100000000000003",
+      "V": "39.4",
+      "AP": "1012.16",
+      "RH": "92.14",
+      "PE": "488.56"
+    },
+    {
+      "AT": "20.86",
+      "V": "57.32",
+      "AP": "1010.24",
+      "RH": "76.64",
+      "PE": "446.48"
+    },
+    {
+      "AT": "10.82",
+      "V": "37.5",
+      "AP": "1009.23",
+      "RH": "96.62",
+      "PE": "473.9"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "primary_family": "tail_rarity_structure",
+    "portability": "yes",
+    "sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "required_roles": [
+      "group_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "n20",
+  "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=V.",
+  "planned_template_id": "tpl_tail_low_support_group_count_v2",
+  "bindings": {
+    "group_col": "V",
+    "top_k": 11,
+    "top_n": 5,
+    "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": 1017.26,
+    "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\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-0879-7ca3-9879-6acefc35fbbb"}
+{"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/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/cli/sql_response_attempt_1.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-0879-7ca3-9879-6acefc35fbbb"}
+{"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/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/cli/sql_response_attempt_2.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-18a1-7890-8ed0-a52fa6daf9b1"}
+{"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/n20/artifacts/v2q_n20_02ffa6f2c1c401bf/cli/sql_response_attempt_2.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40fc-18a1-7890-8ed0-a52fa6daf9b1"}
+{"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/n20/artifacts/v2q_n20_037962f126a9bd60/run_manifest.json

@@ -0,0 +1,72 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n20",
+  "started_at": "2026-05-19T15:59:44.010351+00:00",
+  "ended_at": "2026-05-19T15:59:51.602388+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n20_037962f126a9bd60",
+    "problem_id": "v2p_n20_9aa821118409304f",
+    "dataset_id": "n20",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=V, condition_col=PE.",
+    "bindings": {
+      "group_col": "V",
+      "condition_col": "PE",
+      "condition_value": "434.01",
+      "positive_value": "468.8",
+      "negative_value": "434.01",
+      "top_k": 17,
+      "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": 66.54,
+      "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
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=2/2",
+      "binding_index=97"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 2,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_037962f126a9bd60/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:59:47.203297+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3190.33, "started_at": "2026-05-19T15:59:44.011389+00:00", "ended_at": "2026-05-19T15:59:47.201757+00:00", "prompt_metrics": {"chars": 4799, "bytes_utf8": 4799, "lines": 159, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f6-ea93-79c0-8447-033ca028af64\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:59:51.602290+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3396.41, "started_at": "2026-05-19T15:59:48.205007+00:00", "ended_at": "2026-05-19T15:59:51.601466+00:00", "prompt_metrics": {"chars": 4799, "bytes_utf8": 4799, "lines": 159, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f6-fb11-7bb2-aeb8-1fb8a26e84e1\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_037b53fea1457fc9/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 4546, "bytes_utf8": 4546, "lines": 156, "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": 380, "bytes_utf8": 380, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13519, "cached_input_tokens": 12032, "output_tokens": 365, "reasoning_output_tokens": 255}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_037b53fea1457fc9/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": "n20",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n20_037b53fea1457fc9",
+    "api_calls": 0,
+    "input_tokens": 13519,
+    "cached_input_tokens": 12032,
+    "output_tokens": 365,
+    "total_tokens": 13884,
+    "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": 15184.05,
+    "sql_execution_elapsed_ms_total": 7.58,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_037b53fea1457fc9/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_037b53fea1457fc9/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": "2026-05-19T15:31:19.075068+00:00",
+  "ended_at": "2026-05-19T15:31:34.259154+00:00",
+  "elapsed_ms": 15184.05,
+  "prompt_metrics": {
+    "chars": 4546,
+    "bytes_utf8": 4546,
+    "lines": 156,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1079,
+    "bytes_utf8": 1079,
+    "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": 380,
+      "bytes_utf8": 380,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13519,
+      "cached_input_tokens": 12032,
+      "output_tokens": 365,
+      "reasoning_output_tokens": 255
+    }
+  },
+  "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/n20/artifacts/v2q_n20_037b53fea1457fc9/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,156 @@
+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: n20
+- dataset_name: Combined Cycle Power Plant
+- table_name: n20
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 4 feature columns and target `PE`.
+- task_type: regression
+- target_column: PE
+- main_row_count: 9568
+- important_fields:
+- AT: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AT.
+- V: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate', 'subgroup_candidate'] desc=Numeric field for V.
+- AP: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AP.
+- RH: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for RH.
+- PE: role=target, type=numeric_target. tags=['condition_candidate', 'target_candidate'] desc=Target field for PE.
+- useful_field_combinations: [['V', 'AT', 'PE'], ['AT', 'V', 'PE']]
+- fields_requiring_caution: ['PE', 'AT', 'V', 'AP']
+- source_url: https://archive.ics.uci.edu/dataset/294/combined+cycle+power+plant
+
+SQLite schema snapshot:
+{
+  "table_name": "n20",
+  "quoted_table_name": "\"n20\"",
+  "row_count": 9568,
+  "columns": [
+    {
+      "name": "AT",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "V",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "AP",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "RH",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PE",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "AT": "14.96",
+      "V": "41.76",
+      "AP": "1024.07",
+      "RH": "73.17",
+      "PE": "463.26"
+    },
+    {
+      "AT": "25.18",
+      "V": "62.96",
+      "AP": "1020.04",
+      "RH": "59.08",
+      "PE": "444.37"
+    },
+    {
+      "AT": "5.1100000000000003",
+      "V": "39.4",
+      "AP": "1012.16",
+      "RH": "92.14",
+      "PE": "488.56"
+    },
+    {
+      "AT": "20.86",
+      "V": "57.32",
+      "AP": "1010.24",
+      "RH": "76.64",
+      "PE": "446.48"
+    },
+    {
+      "AT": "10.82",
+      "V": "37.5",
+      "AP": "1009.23",
+      "RH": "96.62",
+      "PE": "473.9"
+    }
+  ]
+}
+
+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": "n20",
+  "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=V, measure_col=RH.",
+  "planned_template_id": "tpl_h2o_group_sum",
+  "bindings": {
+    "group_col": "V",
+    "measure_col": "RH",
+    "top_k": 17,
+    "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": 81.4522,
+    "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/n20/artifacts/v2q_n20_037b53fea1457fc9/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,5 @@
+{"type":"thread.started","thread_id":"019e40dc-e69b-7901-9695-127a71717c50"}
+{"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 14154. Please try again in 424ms. 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_h2o_group_sum\\nSELECT CAST(\\\"V\\\" AS REAL) AS \\\"V\\\", SUM(CAST(\\\"RH\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n20\\\"\\nGROUP BY CAST(\\\"V\\\" AS REAL)\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied the Grouped Numeric Sum template with group_col=\\\"V\\\" and measure_col=\\\"RH\\\". Casted both columns to REAL because the schema stores numeric values as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13519,"cached_input_tokens":12032,"output_tokens":365,"reasoning_output_tokens":255}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_037b53fea1457fc9/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT CAST(\"V\" AS REAL) AS \"V\", SUM(CAST(\"RH\" AS REAL)) AS \"total_measure\"\nFROM \"n20\"\nGROUP BY CAST(\"V\" AS REAL)\nORDER BY \"total_measure\" DESC;","notes":"Applied the Grouped Numeric Sum template with group_col=\"V\" and measure_col=\"RH\". Casted both columns to REAL because the schema stores numeric values as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=V, measure_col=V.
+Result preview: [{"V": 81.56, "percentile_measure": 81.56}, {"V": 80.25, "percentile_measure": 80.25}, {"V": 80.18, "percentile_measure": 80.18}, {"V": 79.74, "percentile_measure": 79.74}, {"V": 79.05, "percentile_measure": 79.05}]

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/generated_sql.sql

@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n20
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_n20_04627e887d026a61
+-- problem_id: v2p_n20_7c81e3148eb5afec
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  CAST("V" AS REAL) AS "V",
+  CAST("V" AS REAL) AS "percentile_measure"
+FROM "n20"
+WHERE "V" IS NOT NULL
+GROUP BY "V"
+ORDER BY "percentile_measure" DESC
+LIMIT 14;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nSELECT\n  CAST(\"V\" AS REAL) AS \"V\",\n  CAST(\"V\" AS REAL) AS \"percentile_measure\"\nFROM \"n20\"\nWHERE \"V\" IS NOT NULL\nGROUP BY \"V\"\nORDER BY \"percentile_measure\" DESC\nLIMIT 14;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nSELECT\\n  CAST(\\\"V\\\" AS REAL) AS \\\"V\\\",\\n  CAST(\\\"V\\\" AS REAL) AS \\\"percentile_measure\\\"\\nFROM \\\"n20\\\"\\nWHERE \\\"V\\\" IS NOT NULL\\nGROUP BY \\\"V\\\"\\nORDER BY \\\"percentile_measure\\\" DESC\\nLIMIT 14;\", \"columns\": [\"V\", \"percentile_measure\"], \"rows\": [{\"V\": 81.56, \"percentile_measure\": 81.56}, {\"V\": 80.25, \"percentile_measure\": 80.25}, {\"V\": 80.18, \"percentile_measure\": 80.18}, {\"V\": 79.74, \"percentile_measure\": 79.74}, {\"V\": 79.05, \"percentile_measure\": 79.05}, {\"V\": 78.92, \"percentile_measure\": 78.92}, {\"V\": 78.87, \"percentile_measure\": 78.87}, {\"V\": 78.11, \"percentile_measure\": 78.11}, {\"V\": 78.05, \"percentile_measure\": 78.05}, {\"V\": 77.95, \"percentile_measure\": 77.95}, {\"V\": 77.54, \"percentile_measure\": 77.54}, {\"V\": 77.3, \"percentile_measure\": 77.3}, {\"V\": 77.24, \"percentile_measure\": 77.24}, {\"V\": 77.17, \"percentile_measure\": 77.17}], \"row_count_returned\": 14, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.62}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n20",
+  "started_at": "2026-05-19T15:55:22.254240+00:00",
+  "ended_at": "2026-05-19T15:55:42.781807+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n20_04627e887d026a61",
+    "problem_id": "v2p_n20_7c81e3148eb5afec",
+    "dataset_id": "n20",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=V, measure_col=V.",
+    "bindings": {
+      "group_col": "V",
+      "measure_col": "V",
+      "top_k": 14,
+      "top_n": 4,
+      "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": 66.54,
+      "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
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=1/2",
+      "binding_index=89"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 6,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/sql/v2q_n20_04627e887d026a61.sql",
+  "usage_summary": {
+    "dataset_id": "n20",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n20_04627e887d026a61",
+    "api_calls": 0,
+    "input_tokens": 13556,
+    "cached_input_tokens": 12672,
+    "output_tokens": 674,
+    "total_tokens": 14230,
+    "cost_usd": 0.0,
+    "ai_cli_calls": 2,
+    "estimated_input_tokens": 0,
+    "estimated_output_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "ai_cli_json_usage",
+    "cli_elapsed_ms_total": 19509.91,
+    "sql_execution_elapsed_ms_total": 10.62,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:55:25.294840+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3038.88, "started_at": "2026-05-19T15:55:22.255322+00:00", "ended_at": "2026-05-19T15:55:25.294225+00:00", "prompt_metrics": {"chars": 4717, "bytes_utf8": 4717, "lines": 156, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-ec3d-7383-9948-1ddf16d9cbb1\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:55:42.768228+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16471.03, "started_at": "2026-05-19T15:55:26.295590+00:00", "ended_at": "2026-05-19T15:55:42.766658+00:00", "prompt_metrics": {"chars": 4717, "bytes_utf8": 4717, "lines": 156, "estimated_tokens": null}, "response_metrics": {"chars": 604, "bytes_utf8": 604, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13556, "cached_input_tokens": 12672, "output_tokens": 674, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nSELECT\\n  CAST(\\\"V\\\" AS REAL) AS \\\"V\\\",\\n  CAST(\\\"V\\\" AS REAL) AS \\\"percentile_measure\\\"\\nFROM \\\"n20\\\"\\nWHERE \\\"V\\\" IS NOT NULL\\nGROUP BY \\\"V\\\"\\nORDER BY \\\"percentile_measure\\\" DESC\\nLIMIT 14;\",\"notes\":\"SQLite does not support PERCENTILE_CONT. Because the grouped column and measure column are both \\\"V\\\", every group contains a single distinct measure value, so the 0.9 percentile within each group is exactly CAST(\\\"V\\\" AS REAL). The query preserves the template intent by grouping on \\\"V\\\" and ranking groups by that percentile-equivalent value.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n20",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n20_04627e887d026a61",
+  "api_calls": 0,
+  "input_tokens": 13556,
+  "cached_input_tokens": 12672,
+  "output_tokens": 674,
+  "total_tokens": 14230,
+  "cost_usd": 0.0,
+  "ai_cli_calls": 2,
+  "estimated_input_tokens": 0,
+  "estimated_output_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "ai_cli_json_usage",
+  "cli_elapsed_ms_total": 19509.91,
+  "sql_execution_elapsed_ms_total": 10.62,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_04627e887d026a61/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_05cdba58ce3ee784/run_manifest.json

@@ -0,0 +1,69 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n20",
+  "started_at": "2026-05-19T15:55:06.941954+00:00",
+  "ended_at": "2026-05-19T15:55:15.225649+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n20_05cdba58ce3ee784",
+    "problem_id": "v2p_n20_1139d7899896cd1f",
+    "dataset_id": "n20",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=V, measure_col=AT.",
+    "bindings": {
+      "group_col": "V",
+      "measure_col": "AT",
+      "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": 25.72,
+      "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
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/2",
+      "binding_index=88"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_05cdba58ce3ee784/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:55:10.009272+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3065.3, "started_at": "2026-05-19T15:55:06.943241+00:00", "ended_at": "2026-05-19T15:55:10.008564+00:00", "prompt_metrics": {"chars": 4721, "bytes_utf8": 4721, "lines": 156, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-b051-7072-9b43-70607153242d\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T15:55:15.225553+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 4214.24, "started_at": "2026-05-19T15:55:11.010528+00:00", "ended_at": "2026-05-19T15:55:15.224811+00:00", "prompt_metrics": {"chars": 4721, "bytes_utf8": 4721, "lines": 156, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-c051-74e3-96e8-b7e5119ba39e\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_077857212da6d6b7/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 4721, "bytes_utf8": 4721, "lines": 156, "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": 1880, "bytes_utf8": 1880, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13556, "cached_input_tokens": 12032, "output_tokens": 3740, "reasoning_output_tokens": 3075}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_077857212da6d6b7/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": "n20",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n20_077857212da6d6b7",
+    "api_calls": 0,
+    "input_tokens": 13556,
+    "cached_input_tokens": 12032,
+    "output_tokens": 3740,
+    "total_tokens": 17296,
+    "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": 63777.74,
+    "sql_execution_elapsed_ms_total": 35.6,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_077857212da6d6b7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_077857212da6d6b7/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": "2026-05-19T15:57:42.906905+00:00",
+  "ended_at": "2026-05-19T15:58:46.684673+00:00",
+  "elapsed_ms": 63777.74,
+  "prompt_metrics": {
+    "chars": 4721,
+    "bytes_utf8": 4721,
+    "lines": 156,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 2524,
+    "bytes_utf8": 2524,
+    "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": 1880,
+      "bytes_utf8": 1880,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13556,
+      "cached_input_tokens": 12032,
+      "output_tokens": 3740,
+      "reasoning_output_tokens": 3075
+    }
+  },
+  "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/n20/artifacts/v2q_n20_077857212da6d6b7/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,156 @@
+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: n20
+- dataset_name: Combined Cycle Power Plant
+- table_name: n20
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 4 feature columns and target `PE`.
+- task_type: regression
+- target_column: PE
+- main_row_count: 9568
+- important_fields:
+- AT: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AT.
+- V: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate', 'subgroup_candidate'] desc=Numeric field for V.
+- AP: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AP.
+- RH: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for RH.
+- PE: role=target, type=numeric_target. tags=['condition_candidate', 'target_candidate'] desc=Target field for PE.
+- useful_field_combinations: [['V', 'AT', 'PE'], ['AT', 'V', 'PE']]
+- fields_requiring_caution: ['PE', 'AT', 'V', 'AP']
+- source_url: https://archive.ics.uci.edu/dataset/294/combined+cycle+power+plant
+
+SQLite schema snapshot:
+{
+  "table_name": "n20",
+  "quoted_table_name": "\"n20\"",
+  "row_count": 9568,
+  "columns": [
+    {
+      "name": "AT",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "V",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "AP",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "RH",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PE",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "AT": "14.96",
+      "V": "41.76",
+      "AP": "1024.07",
+      "RH": "73.17",
+      "PE": "463.26"
+    },
+    {
+      "AT": "25.18",
+      "V": "62.96",
+      "AP": "1020.04",
+      "RH": "59.08",
+      "PE": "444.37"
+    },
+    {
+      "AT": "5.1100000000000003",
+      "V": "39.4",
+      "AP": "1012.16",
+      "RH": "92.14",
+      "PE": "488.56"
+    },
+    {
+      "AT": "20.86",
+      "V": "57.32",
+      "AP": "1010.24",
+      "RH": "76.64",
+      "PE": "446.48"
+    },
+    {
+      "AT": "10.82",
+      "V": "37.5",
+      "AP": "1009.23",
+      "RH": "96.62",
+      "PE": "473.9"
+    }
+  ]
+}
+
+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": "n20",
+  "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=V, measure_col=AT.",
+  "planned_template_id": "tpl_grouped_percentile_point",
+  "bindings": {
+    "group_col": "V",
+    "measure_col": "AT",
+    "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": 25.72,
+    "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_a/n20/artifacts/v2q_n20_077857212da6d6b7/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f5-117b-7cc3-9c78-43153e732fd9"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n  SELECT\\n    CAST(\\\"V\\\" AS REAL) AS \\\"V_num\\\",\\n    CAST(\\\"AT\\\" AS REAL) AS \\\"AT_num\\\"\\n  FROM \\\"n20\\\"\\n  WHERE \\\"V\\\" IS NOT NULL\\n    AND \\\"AT\\\" IS NOT NULL\\n),\\n\\\"ranked\\\" AS (\\n  SELECT\\n    \\\"V_num\\\",\\n    \\\"AT_num\\\",\\n    ROW_NUMBER() OVER (PARTITION BY \\\"V_num\\\" ORDER BY \\\"AT_num\\\") AS \\\"rn\\\",\\n    COUNT(*) OVER (PARTITION BY \\\"V_num\\\") AS \\\"cnt\\\"\\n  FROM \\\"base\\\"\\n),\\n\\\"params\\\" AS (\\n  SELECT DISTINCT\\n    \\\"V_num\\\",\\n    \\\"cnt\\\",\\n    ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS \\\"h\\\",\\n    CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) AS \\\"lower_rn\\\",\\n    CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) + CASE\\n      WHEN ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) > CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) THEN 1\\n      ELSE 0\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cnt\\\" >= 5\\n),\\n\\\"bounds\\\" AS (\\n  SELECT\\n    p.\\\"V_num\\\",\\n    p.\\\"cnt\\\",\\n    p.\\\"h\\\",\\n    MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"AT_num\\\" END) AS \\\"lower_val\\\",\\n    MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN r.\\\"AT_num\\\" END) AS \\\"upper_val\\\"\\n  FROM \\\"params\\\" AS p\\n  JOIN \\\"ranked\\\" AS r\\n    ON r.\\\"V_num\\\" = p.\\\"V_num\\\"\\n  GROUP BY p.\\\"V_num\\\", p.\\\"cnt\\\", p.\\\"h\\\"\\n)\\nSELECT\\n  \\\"V_num\\\" AS \\\"V\\\",\\n  CASE\\n    WHEN \\\"lower_val\\\" IS NULL THEN NULL\\n    WHEN \\\"upper_val\\\" IS NULL THEN \\\"lower_val\\\"\\n    WHEN \\\"h\\\" = CAST(\\\"h\\\" AS INTEGER) THEN \\\"lower_val\\\"\\n    ELSE \\\"lower_val\\\" + ((\\\"h\\\" - CAST(\\\"h\\\" AS INTEGER)) * (\\\"upper_val\\\" - \\\"lower_val\\\"))\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\"\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"V\\\" DESC\\nLIMIT 12;\",\"notes\":\"Emulates PERCENTILE_CONT(0.95) in SQLite with window ranks and linear interpolation, casts text-stored numeric fields to REAL, enforces a minimum group size of 5, and returns the top 12 V groups by 95th-percentile AT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13556,"cached_input_tokens":12032,"output_tokens":3740,"reasoning_output_tokens":3075}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_077857212da6d6b7/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n  SELECT\n    CAST(\"V\" AS REAL) AS \"V_num\",\n    CAST(\"AT\" AS REAL) AS \"AT_num\"\n  FROM \"n20\"\n  WHERE \"V\" IS NOT NULL\n    AND \"AT\" IS NOT NULL\n),\n\"ranked\" AS (\n  SELECT\n    \"V_num\",\n    \"AT_num\",\n    ROW_NUMBER() OVER (PARTITION BY \"V_num\" ORDER BY \"AT_num\") AS \"rn\",\n    COUNT(*) OVER (PARTITION BY \"V_num\") AS \"cnt\"\n  FROM \"base\"\n),\n\"params\" AS (\n  SELECT DISTINCT\n    \"V_num\",\n    \"cnt\",\n    ((0.95 * (\"cnt\" - 1)) + 1.0) AS \"h\",\n    CAST(((0.95 * (\"cnt\" - 1)) + 1.0) AS INTEGER) AS \"lower_rn\",\n    CAST(((0.95 * (\"cnt\" - 1)) + 1.0) AS INTEGER) + CASE\n      WHEN ((0.95 * (\"cnt\" - 1)) + 1.0) > CAST(((0.95 * (\"cnt\" - 1)) + 1.0) AS INTEGER) THEN 1\n      ELSE 0\n    END AS \"upper_rn\"\n  FROM \"ranked\"\n  WHERE \"cnt\" >= 5\n),\n\"bounds\" AS (\n  SELECT\n    p.\"V_num\",\n    p.\"cnt\",\n    p.\"h\",\n    MAX(CASE WHEN r.\"rn\" = p.\"lower_rn\" THEN r.\"AT_num\" END) AS \"lower_val\",\n    MAX(CASE WHEN r.\"rn\" = p.\"upper_rn\" THEN r.\"AT_num\" END) AS \"upper_val\"\n  FROM \"params\" AS p\n  JOIN \"ranked\" AS r\n    ON r.\"V_num\" = p.\"V_num\"\n  GROUP BY p.\"V_num\", p.\"cnt\", p.\"h\"\n)\nSELECT\n  \"V_num\" AS \"V\",\n  CASE\n    WHEN \"lower_val\" IS NULL THEN NULL\n    WHEN \"upper_val\" IS NULL THEN \"lower_val\"\n    WHEN \"h\" = CAST(\"h\" AS INTEGER) THEN \"lower_val\"\n    ELSE \"lower_val\" + ((\"h\" - CAST(\"h\" AS INTEGER)) * (\"upper_val\" - \"lower_val\"))\n  END AS \"percentile_measure\"\nFROM \"bounds\"\nORDER BY \"percentile_measure\" DESC, \"V\" DESC\nLIMIT 12;","notes":"Emulates PERCENTILE_CONT(0.95) in SQLite with window ranks and linear interpolation, casts text-stored numeric fields to REAL, enforces a minimum group size of 5, and returns the top 12 V groups by 95th-percentile AT."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 4807, "bytes_utf8": 4807, "lines": 159, "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": 434, "bytes_utf8": 434, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13587, "cached_input_tokens": 12032, "output_tokens": 642, "reasoning_output_tokens": 516}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/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": "n20",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n20_098153d19f5dc9e6",
+    "api_calls": 0,
+    "input_tokens": 13587,
+    "cached_input_tokens": 12032,
+    "output_tokens": 642,
+    "total_tokens": 14229,
+    "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": 15060.99,
+    "sql_execution_elapsed_ms_total": 7.68,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/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": "2026-05-19T15:59:51.603908+00:00",
+  "ended_at": "2026-05-19T16:00:06.664929+00:00",
+  "elapsed_ms": 15060.99,
+  "prompt_metrics": {
+    "chars": 4807,
+    "bytes_utf8": 4807,
+    "lines": 159,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 801,
+    "bytes_utf8": 801,
+    "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": 434,
+      "bytes_utf8": 434,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 13587,
+      "cached_input_tokens": 12032,
+      "output_tokens": 642,
+      "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_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,159 @@
+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: n20
+- dataset_name: Combined Cycle Power Plant
+- table_name: n20
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 4 feature columns and target `PE`.
+- task_type: regression
+- target_column: PE
+- main_row_count: 9568
+- important_fields:
+- AT: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AT.
+- V: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate', 'subgroup_candidate'] desc=Numeric field for V.
+- AP: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for AP.
+- RH: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for RH.
+- PE: role=target, type=numeric_target. tags=['condition_candidate', 'target_candidate'] desc=Target field for PE.
+- useful_field_combinations: [['V', 'AT', 'PE'], ['AT', 'V', 'PE']]
+- fields_requiring_caution: ['PE', 'AT', 'V', 'AP']
+- source_url: https://archive.ics.uci.edu/dataset/294/combined+cycle+power+plant
+
+SQLite schema snapshot:
+{
+  "table_name": "n20",
+  "quoted_table_name": "\"n20\"",
+  "row_count": 9568,
+  "columns": [
+    {
+      "name": "AT",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "V",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "AP",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "RH",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "PE",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "AT": "14.96",
+      "V": "41.76",
+      "AP": "1024.07",
+      "RH": "73.17",
+      "PE": "463.26"
+    },
+    {
+      "AT": "25.18",
+      "V": "62.96",
+      "AP": "1020.04",
+      "RH": "59.08",
+      "PE": "444.37"
+    },
+    {
+      "AT": "5.1100000000000003",
+      "V": "39.4",
+      "AP": "1012.16",
+      "RH": "92.14",
+      "PE": "488.56"
+    },
+    {
+      "AT": "20.86",
+      "V": "57.32",
+      "AP": "1010.24",
+      "RH": "76.64",
+      "PE": "446.48"
+    },
+    {
+      "AT": "10.82",
+      "V": "37.5",
+      "AP": "1009.23",
+      "RH": "96.62",
+      "PE": "473.9"
+    }
+  ]
+}
+
+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": "n20",
+  "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=V, condition_col=PE.",
+  "planned_template_id": "tpl_m4_group_condition_rate",
+  "bindings": {
+    "group_col": "V",
+    "condition_col": "PE",
+    "condition_value": "468.8",
+    "positive_value": "468.8",
+    "negative_value": "434.01",
+    "top_k": 13,
+    "top_n": 5,
+    "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": 1017.26,
+    "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/n20/artifacts/v2q_n20_098153d19f5dc9e6/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40f7-0858-7b40-8506-ee0c554a6bf9"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT CAST(\\\"V\\\" AS REAL) AS \\\"V\\\",\\n       AVG(CASE WHEN CAST(\\\"PE\\\" AS REAL) = 468.8 THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n20\\\"\\nGROUP BY CAST(\\\"V\\\" AS REAL)\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the Grouped Condition Rate template with group_col=\\\"V\\\" and condition_col=\\\"PE\\\". CAST to REAL is used because the schema stores numeric fields as TEXT.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":13587,"cached_input_tokens":12032,"output_tokens":642,"reasoning_output_tokens":516}}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT CAST(\"V\" AS REAL) AS \"V\",\n       AVG(CASE WHEN CAST(\"PE\" AS REAL) = 468.8 THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"n20\"\nGROUP BY CAST(\"V\" AS REAL)\nORDER BY \"condition_rate\" DESC;","notes":"Applied the Grouped Condition Rate template with group_col=\"V\" and condition_col=\"PE\". CAST to REAL is used because the schema stores numeric fields as TEXT."}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=V, condition_col=PE.
+Result preview: [{"V": 44.34, "condition_rate": 0.30434782608695654}, {"V": 43.34, "condition_rate": 0.05555555555555555}, {"V": 40.89, "condition_rate": 0.05}, {"V": 81.56, "condition_rate": 0.0}, {"V": 80.25, "condition_rate": 0.0}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/generated_sql.sql

@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n20
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: dependency_strength_similarity
+-- intended_facet_id: pairwise_conditional_dependency
+-- variant_semantic_role: within_group_proportion
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n20_098153d19f5dc9e6
+-- problem_id: v2p_n20_9ad3e59b59173cd4
+-- realization_mode: agent
+-- source_kind: agent
+SELECT CAST("V" AS REAL) AS "V",
+       AVG(CASE WHEN CAST("PE" AS REAL) = 468.8 THEN 1 ELSE 0 END) AS "condition_rate"
+FROM "n20"
+GROUP BY CAST("V" AS REAL)
+ORDER BY "condition_rate" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n20/artifacts/v2q_n20_098153d19f5dc9e6/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT CAST(\"V\" AS REAL) AS \"V\",\n       AVG(CASE WHEN CAST(\"PE\" AS REAL) = 468.8 THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"n20\"\nGROUP BY CAST(\"V\" AS REAL)\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT CAST(\\\"V\\\" AS REAL) AS \\\"V\\\",\\n       AVG(CASE WHEN CAST(\\\"PE\\\" AS REAL) = 468.8 THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n20\\\"\\nGROUP BY CAST(\\\"V\\\" AS REAL)\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"V\", \"condition_rate\"], \"rows\": [{\"V\": 44.34, \"condition_rate\": 0.30434782608695654}, {\"V\": 43.34, \"condition_rate\": 0.05555555555555555}, {\"V\": 40.89, \"condition_rate\": 0.05}, {\"V\": 81.56, \"condition_rate\": 0.0}, {\"V\": 80.25, \"condition_rate\": 0.0}, {\"V\": 80.18, \"condition_rate\": 0.0}, {\"V\": 79.74, \"condition_rate\": 0.0}, {\"V\": 79.05, \"condition_rate\": 0.0}, {\"V\": 78.92, \"condition_rate\": 0.0}, {\"V\": 78.87, \"condition_rate\": 0.0}, {\"V\": 78.11, \"condition_rate\": 0.0}, {\"V\": 78.05, \"condition_rate\": 0.0}, {\"V\": 77.95, \"condition_rate\": 0.0}, {\"V\": 77.54, \"condition_rate\": 0.0}, {\"V\": 77.3, \"condition_rate\": 0.0}, {\"V\": 77.24, \"condition_rate\": 0.0}, {\"V\": 77.17, \"condition_rate\": 0.0}, {\"V\": 76.86, \"condition_rate\": 0.0}, {\"V\": 76.2, \"condition_rate\": 0.0}, {\"V\": 76.16, \"condition_rate\": 0.0}, {\"V\": 76.09, \"condition_rate\": 0.0}, {\"V\": 75.6, \"condition_rate\": 0.0}, {\"V\": 75.33, \"condition_rate\": 0.0}, {\"V\": 75.23, \"condition_rate\": 0.0}, {\"V\": 75.08, \"condition_rate\": 0.0}, {\"V\": 74.99, \"condition_rate\": 0.0}, {\"V\": 74.93, \"condition_rate\": 0.0}, {\"V\": 74.9, \"condition_rate\": 0.0}, {\"V\": 74.87, \"condition_rate\": 0.0}, {\"V\": 74.78, \"condition_rate\": 0.0}, {\"V\": 74.67, \"condition_rate\": 0.0}, {\"V\": 74.34, \"condition_rate\": 0.0}, {\"V\": 74.33, \"condition_rate\": 0.0}, {\"V\": 74.22, \"condition_rate\": 0.0}, {\"V\": 74.16, \"condition_rate\": 0.0}, {\"V\": 73.91, \"condition_rate\": 0.0}, {\"V\": 73.9, \"condition_rate\": 0.0}, {\"V\": 73.88, \"condition_rate\": 0.0}, {\"V\": 73.77, \"condition_rate\": 0.0}, {\"V\": 73.68, \"condition_rate\": 0.0}, {\"V\": 73.67, \"condition_rate\": 0.0}, {\"V\": 73.56, \"condition_rate\": 0.0}, {\"V\": 73.5, \"condition_rate\": 0.0}, {\"V\": 73.46, \"condition_rate\": 0.0}, {\"V\": 73.42, \"condition_rate\": 0.0}, {\"V\": 73.4, \"condition_rate\": 0.0}, {\"V\": 73.21, \"condition_rate\": 0.0}, {\"V\": 73.18, \"condition_rate\": 0.0}, {\"V\": 73.17, \"condition_rate\": 0.0}, {\"V\": 73.11, \"condition_rate\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.68}"}