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Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=four_g, measure_col=mobile_wt.
+Result preview: [{"four_g": "1", "total_measure": 145695.0}, {"four_g": "0", "total_measure": 134803.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: m10
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_m10_024b6dfade6006ef
+-- problem_id: v2p_m10_cabe7bb907faf806
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "four_g", SUM(CAST("mobile_wt" AS REAL)) AS total_measure
+FROM "m10"
+GROUP BY "four_g"
+ORDER BY total_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/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_h2o_group_sum\nSELECT \"four_g\", SUM(CAST(\"mobile_wt\" AS REAL)) AS total_measure\nFROM \"m10\"\nGROUP BY \"four_g\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"four_g\\\", SUM(CAST(\\\"mobile_wt\\\" AS REAL)) AS total_measure\\nFROM \\\"m10\\\"\\nGROUP BY \\\"four_g\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"four_g\", \"total_measure\"], \"rows\": [{\"four_g\": \"1\", \"total_measure\": 145695.0}, {\"four_g\": \"0\", \"total_measure\": 134803.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.15}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T15:29:47.329692+00:00",
+  "ended_at": "2026-05-19T15:29:57.112251+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_024b6dfade6006ef",
+    "problem_id": "v2p_m10_cabe7bb907faf806",
+    "dataset_id": "m10",
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_rank_order",
+    "variant_semantic_role": "collapsed_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=four_g, measure_col=mobile_wt.",
+    "bindings": {
+      "group_col": "four_g",
+      "measure_col": "mobile_wt",
+      "top_k": 14,
+      "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": 170.0,
+      "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
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=1/2",
+      "binding_index=4"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "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",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/sql/v2q_m10_024b6dfade6006ef.sql",
+  "usage_summary": {
+    "dataset_id": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_024b6dfade6006ef",
+    "api_calls": 0,
+    "input_tokens": 15219,
+    "cached_input_tokens": 12032,
+    "output_tokens": 240,
+    "total_tokens": 15459,
+    "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": 9777.61,
+    "sql_execution_elapsed_ms_total": 1.15,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:29:57.109633+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": 9777.61, "started_at": "2026-05-19T15:29:47.330775+00:00", "ended_at": "2026-05-19T15:29:57.108411+00:00", "prompt_metrics": {"chars": 10509, "bytes_utf8": 10509, "lines": 348, "estimated_tokens": null}, "response_metrics": {"chars": 371, "bytes_utf8": 371, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15219, "cached_input_tokens": 12032, "output_tokens": 240, "reasoning_output_tokens": 137}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"four_g\\\", SUM(CAST(\\\"mobile_wt\\\" AS REAL)) AS total_measure\\nFROM \\\"m10\\\"\\nGROUP BY \\\"four_g\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the provided grouped numeric sum template with group_col=\\\"four_g\\\" and measure_col=\\\"mobile_wt\\\". Cast \\\"mobile_wt\\\" to REAL because the schema snapshot stores columns as TEXT.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "m10",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_m10_024b6dfade6006ef",
+  "api_calls": 0,
+  "input_tokens": 15219,
+  "cached_input_tokens": 12032,
+  "output_tokens": 240,
+  "total_tokens": 15459,
+  "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": 9777.61,
+  "sql_execution_elapsed_ms_total": 1.15,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_024b6dfade6006ef/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=price_range, condition_col=price_range.
+Result preview: [{"price_range": "1", "condition_ratio": 0.0}, {"price_range": "0", "condition_ratio": null}, {"price_range": "2", "condition_ratio": null}, {"price_range": "3", "condition_ratio": null}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/generated_sql.sql

@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: m10
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: contrastive_conditional_view
+-- template_id: tpl_m4_group_ratio_two_conditions
+-- query_record_id: v2q_m10_08128d2224ba1fe7
+-- problem_id: v2p_m10_99cdbe8b72476491
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "price_range",
+           SUM(CASE WHEN "price_range" = '0' THEN 1 ELSE 0 END) AS numerator_count,
+           SUM(CASE WHEN "price_range" = '1' THEN 1 ELSE 0 END) AS denominator_count
+    FROM "m10"
+    GROUP BY "price_range"
+)
+SELECT "price_range",
+       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio
+FROM grouped
+ORDER BY condition_ratio DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/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_ratio_two_conditions\nWITH grouped AS (\n    SELECT \"price_range\",\n           SUM(CASE WHEN \"price_range\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN \"price_range\" = '1' THEN 1 ELSE 0 END) AS denominator_count\n    FROM \"m10\"\n    GROUP BY \"price_range\"\n)\nSELECT \"price_range\",\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"price_range\\\",\\n           SUM(CASE WHEN \\\"price_range\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"price_range\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"m10\\\"\\n    GROUP BY \\\"price_range\\\"\\n)\\nSELECT \\\"price_range\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"price_range\", \"condition_ratio\"], \"rows\": [{\"price_range\": \"1\", \"condition_ratio\": 0.0}, {\"price_range\": \"0\", \"condition_ratio\": null}, {\"price_range\": \"2\", \"condition_ratio\": null}, {\"price_range\": \"3\", \"condition_ratio\": null}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.26}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/run_manifest.json

@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T15:40:40.580344+00:00",
+  "ended_at": "2026-05-19T15:40:55.632326+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_08128d2224ba1fe7",
+    "problem_id": "v2p_m10_99cdbe8b72476491",
+    "dataset_id": "m10",
+    "template_id": "tpl_m4_group_ratio_two_conditions",
+    "template_name": "Grouped Ratio of Two Conditions",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "variant_semantic_role": "contrastive_conditional_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=price_range, condition_col=price_range.",
+    "bindings": {
+      "group_col": "price_range",
+      "condition_col": "price_range",
+      "condition_value": "0",
+      "positive_value": "0",
+      "negative_value": "1",
+      "top_k": 14,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 7.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col},\n           SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n           SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT {group_col},\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;",
+    "notes": [
+      "default_facets=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=9",
+      "sql_variant_index=1/1",
+      "binding_index=44"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 4,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "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_b/m10/sql/v2q_m10_08128d2224ba1fe7.sql",
+  "usage_summary": {
+    "dataset_id": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_08128d2224ba1fe7",
+    "api_calls": 0,
+    "input_tokens": 15426,
+    "cached_input_tokens": 12032,
+    "output_tokens": 705,
+    "total_tokens": 16131,
+    "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": 15046.75,
+    "sql_execution_elapsed_ms_total": 1.26,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:40:55.629478+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": 15046.75, "started_at": "2026-05-19T15:40:40.581292+00:00", "ended_at": "2026-05-19T15:40:55.628074+00:00", "prompt_metrics": {"chars": 11327, "bytes_utf8": 11327, "lines": 351, "estimated_tokens": null}, "response_metrics": {"chars": 746, "bytes_utf8": 746, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15426, "cached_input_tokens": 12032, "output_tokens": 705, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n    SELECT \\\"price_range\\\",\\n           SUM(CASE WHEN \\\"price_range\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n           SUM(CASE WHEN \\\"price_range\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n    FROM \\\"m10\\\"\\n    GROUP BY \\\"price_range\\\"\\n)\\nSELECT \\\"price_range\\\",\\n       CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Used the provided grouped ratio template with both group_col and condition_col bound to \\\"price_range\\\", and compared positive_value '0' against negative_value '1' using SQLite-compatible CASE aggregation and NULLIF to avoid division by zero.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "m10",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_m10_08128d2224ba1fe7",
+  "api_calls": 0,
+  "input_tokens": 15426,
+  "cached_input_tokens": 12032,
+  "output_tokens": 705,
+  "total_tokens": 16131,
+  "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": 15046.75,
+  "sql_execution_elapsed_ms_total": 1.26,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_08128d2224ba1fe7/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=four_g.
+Result preview: [{"four_g": "1", "row_count": 1043}, {"four_g": "0", "row_count": 957}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: m10
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_m10_0b9224f94410f843
+-- problem_id: v2p_m10_ad68c31ef1c25b4e
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "four_g", COUNT(*) AS row_count
+FROM "m10"
+GROUP BY "four_g"
+ORDER BY row_count DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/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_clickbench_group_count\nSELECT \"four_g\", COUNT(*) AS row_count\nFROM \"m10\"\nGROUP BY \"four_g\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"four_g\\\", COUNT(*) AS row_count\\nFROM \\\"m10\\\"\\nGROUP BY \\\"four_g\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"four_g\", \"row_count\"], \"rows\": [{\"four_g\": \"1\", \"row_count\": 1043}, {\"four_g\": \"0\", \"row_count\": 957}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.9}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T15:33:25.668509+00:00",
+  "ended_at": "2026-05-19T15:33:33.149617+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_0b9224f94410f843",
+    "problem_id": "v2p_m10_ad68c31ef1c25b4e",
+    "dataset_id": "m10",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=four_g.",
+    "bindings": {
+      "group_col": "four_g",
+      "top_k": 14,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 7.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/1",
+      "binding_index=19"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 8,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "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_b/m10/sql/v2q_m10_0b9224f94410f843.sql",
+  "usage_summary": {
+    "dataset_id": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_0b9224f94410f843",
+    "api_calls": 0,
+    "input_tokens": 15190,
+    "cached_input_tokens": 12032,
+    "output_tokens": 251,
+    "total_tokens": 15441,
+    "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": 7473.96,
+    "sql_execution_elapsed_ms_total": 1.9,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:33:33.145112+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": 7473.96, "started_at": "2026-05-19T15:33:25.669508+00:00", "ended_at": "2026-05-19T15:33:33.143507+00:00", "prompt_metrics": {"chars": 10414, "bytes_utf8": 10414, "lines": 346, "estimated_tokens": null}, "response_metrics": {"chars": 279, "bytes_utf8": 279, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15190, "cached_input_tokens": 12032, "output_tokens": 251, "reasoning_output_tokens": 177}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"four_g\\\", COUNT(*) AS row_count\\nFROM \\\"m10\\\"\\nGROUP BY \\\"four_g\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Uses the planned grouped-count template with group_col bound to \\\"four_g\\\" to inspect subgroup size distribution.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "m10",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_m10_0b9224f94410f843",
+  "api_calls": 0,
+  "input_tokens": 15190,
+  "cached_input_tokens": 12032,
+  "output_tokens": 251,
+  "total_tokens": 15441,
+  "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": 7473.96,
+  "sql_execution_elapsed_ms_total": 1.9,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0b9224f94410f843/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=fc.
+Result preview: [{"fc": "0", "row_count": 474}, {"fc": "1", "row_count": 245}, {"fc": "2", "row_count": 189}, {"fc": "3", "row_count": 170}, {"fc": "5", "row_count": 139}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: m10
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_m10_0bde49f42a6f34e8
+-- problem_id: v2p_m10_8421b47c15d810ec
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "fc", COUNT(*) AS "row_count"
+FROM "m10"
+GROUP BY "fc"
+ORDER BY "row_count" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/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_clickbench_group_count\nSELECT \"fc\", COUNT(*) AS \"row_count\"\nFROM \"m10\"\nGROUP BY \"fc\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"fc\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m10\\\"\\nGROUP BY \\\"fc\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"fc\", \"row_count\"], \"rows\": [{\"fc\": \"0\", \"row_count\": 474}, {\"fc\": \"1\", \"row_count\": 245}, {\"fc\": \"2\", \"row_count\": 189}, {\"fc\": \"3\", \"row_count\": 170}, {\"fc\": \"5\", \"row_count\": 139}, {\"fc\": \"4\", \"row_count\": 133}, {\"fc\": \"6\", \"row_count\": 112}, {\"fc\": \"7\", \"row_count\": 100}, {\"fc\": \"9\", \"row_count\": 78}, {\"fc\": \"8\", \"row_count\": 77}, {\"fc\": \"10\", \"row_count\": 62}, {\"fc\": \"11\", \"row_count\": 51}, {\"fc\": \"12\", \"row_count\": 45}, {\"fc\": \"13\", \"row_count\": 40}, {\"fc\": \"16\", \"row_count\": 24}, {\"fc\": \"15\", \"row_count\": 23}, {\"fc\": \"14\", \"row_count\": 20}, {\"fc\": \"18\", \"row_count\": 11}, {\"fc\": \"17\", \"row_count\": 6}, {\"fc\": \"19\", \"row_count\": 1}], \"row_count_returned\": 20, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.03}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T15:33:04.993217+00:00",
+  "ended_at": "2026-05-19T15:33:25.667938+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_0bde49f42a6f34e8",
+    "problem_id": "v2p_m10_8421b47c15d810ec",
+    "dataset_id": "m10",
+    "template_id": "tpl_clickbench_group_count",
+    "template_name": "Grouped Count by Category",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "subgroup_size_stability",
+    "intended_facet_id": "subgroup_distribution_shift",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=fc.",
+    "bindings": {
+      "group_col": "fc",
+      "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": 170.0,
+      "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
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=1/1",
+      "binding_index=18"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 2,
+    "problem_index_within_template": 7,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "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_b/m10/sql/v2q_m10_0bde49f42a6f34e8.sql",
+  "usage_summary": {
+    "dataset_id": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_0bde49f42a6f34e8",
+    "api_calls": 0,
+    "input_tokens": 15188,
+    "cached_input_tokens": 12032,
+    "output_tokens": 358,
+    "total_tokens": 15546,
+    "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": 20670.72,
+    "sql_execution_elapsed_ms_total": 1.03,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:33:25.665740+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": 20670.72, "started_at": "2026-05-19T15:33:04.994286+00:00", "ended_at": "2026-05-19T15:33:25.665027+00:00", "prompt_metrics": {"chars": 10409, "bytes_utf8": 10409, "lines": 346, "estimated_tokens": null}, "response_metrics": {"chars": 270, "bytes_utf8": 270, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15188, "cached_input_tokens": 12032, "output_tokens": 358, "reasoning_output_tokens": 284}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"fc\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m10\\\"\\nGROUP BY \\\"fc\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Counts rows for each distinct value of \\\"fc\\\" to examine subgroup count distribution and size stability.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "m10",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_m10_0bde49f42a6f34e8",
+  "api_calls": 0,
+  "input_tokens": 15188,
+  "cached_input_tokens": 12032,
+  "output_tokens": 358,
+  "total_tokens": 15546,
+  "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": 20670.72,
+  "sql_execution_elapsed_ms_total": 1.03,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0bde49f42a6f34e8/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/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=touch_screen, condition_col=four_g.
+Result preview: [{"touch_screen": "0", "condition_rate": 0.4869215291750503}, {"touch_screen": "1", "condition_rate": 0.4701789264413519}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/generated_sql.sql

@@ -0,0 +1,18 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: m10
+-- 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_m10_0c396a6af72ff036
+-- problem_id: v2p_m10_8663f0d38ec49fad
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "touch_screen",
+       AVG(CASE WHEN "four_g" = '0' THEN 1 ELSE 0 END) AS condition_rate
+FROM "m10"
+GROUP BY "touch_screen"
+ORDER BY condition_rate DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/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 \"touch_screen\",\n       AVG(CASE WHEN \"four_g\" = '0' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m10\"\nGROUP BY \"touch_screen\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"touch_screen\\\",\\n       AVG(CASE WHEN \\\"four_g\\\" = '0' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m10\\\"\\nGROUP BY \\\"touch_screen\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"touch_screen\", \"condition_rate\"], \"rows\": [{\"touch_screen\": \"0\", \"condition_rate\": 0.4869215291750503}, {\"touch_screen\": \"1\", \"condition_rate\": 0.4701789264413519}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.08}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/run_manifest.json

@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T16:01:28.954908+00:00",
+  "ended_at": "2026-05-19T16:01:38.618410+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_0c396a6af72ff036",
+    "problem_id": "v2p_m10_8663f0d38ec49fad",
+    "dataset_id": "m10",
+    "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=touch_screen, condition_col=four_g.",
+    "bindings": {
+      "group_col": "touch_screen",
+      "condition_col": "four_g",
+      "condition_value": "0",
+      "positive_value": "1",
+      "negative_value": "0",
+      "top_k": 17,
+      "top_n": 6,
+      "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": 170.0,
+      "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
+    },
+    "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=7",
+      "sql_variant_index=2/2",
+      "binding_index=102"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 7,
+    "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_b/m10/sql/v2q_m10_0c396a6af72ff036.sql",
+  "usage_summary": {
+    "dataset_id": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_0c396a6af72ff036",
+    "api_calls": 0,
+    "input_tokens": 15278,
+    "cached_input_tokens": 12032,
+    "output_tokens": 335,
+    "total_tokens": 15613,
+    "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": 9657.49,
+    "sql_execution_elapsed_ms_total": 1.08,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T16:01:38.615705+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": 9657.49, "started_at": "2026-05-19T16:01:28.957399+00:00", "ended_at": "2026-05-19T16:01:38.614926+00:00", "prompt_metrics": {"chars": 10762, "bytes_utf8": 10762, "lines": 351, "estimated_tokens": null}, "response_metrics": {"chars": 425, "bytes_utf8": 425, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15278, "cached_input_tokens": 12032, "output_tokens": 335, "reasoning_output_tokens": 223}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"touch_screen\\\",\\n       AVG(CASE WHEN \\\"four_g\\\" = '0' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m10\\\"\\nGROUP BY \\\"touch_screen\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Uses the planned Grouped Condition Rate template with group_col=\\\"touch_screen\\\" and condition_col=\\\"four_g\\\", comparing against the bound condition_value '0' as text to match the schema.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "m10",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_m10_0c396a6af72ff036",
+  "api_calls": 0,
+  "input_tokens": 15278,
+  "cached_input_tokens": 12032,
+  "output_tokens": 335,
+  "total_tokens": 15613,
+  "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": 9657.49,
+  "sql_execution_elapsed_ms_total": 1.08,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c396a6af72ff036/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0c6d673f80ad599b/run_manifest.json

@@ -0,0 +1,69 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T16:06:14.070807+00:00",
+  "ended_at": "2026-05-19T16:06:21.298175+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_0c6d673f80ad599b",
+    "problem_id": "v2p_m10_7042c10a09cd53c7",
+    "dataset_id": "m10",
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "slice_level_consistency",
+    "intended_facet_id": "conditional_interaction_hotspots",
+    "variant_semantic_role": "filtered_stable_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=touch_screen, measure_col=pc.",
+    "bindings": {
+      "group_col": "touch_screen",
+      "measure_col": "pc",
+      "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": 15.0,
+      "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
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n       AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
+    "notes": [
+      "default_facets=conditional_interaction_hotspots",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/2",
+      "binding_index=132"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 12,
+    "problem_index_within_template": 1,
+    "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_b/m10/artifacts/v2q_m10_0c6d673f80ad599b/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:06:16.934121+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": 2861.64, "started_at": "2026-05-19T16:06:14.071773+00:00", "ended_at": "2026-05-19T16:06:16.933437+00:00", "prompt_metrics": {"chars": 10592, "bytes_utf8": 10592, "lines": 348, "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\":\"019e40fc-de3d-79f0-8b73-3d8bedf0cd0b\"}\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": "2026-05-19T16:06:21.298080+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": 3361.46, "started_at": "2026-05-19T16:06:17.935797+00:00", "ended_at": "2026-05-19T16:06:21.297304+00:00", "prompt_metrics": {"chars": 10592, "bytes_utf8": 10592, "lines": 348, "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\":\"019e40fc-ed45-7c40-b943-e8f79f98437e\"}\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_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=px_height.
+Result preview: [{"px_height": "1960"}, {"px_height": "1949"}, {"px_height": "1920"}, {"px_height": "1914"}, {"px_height": "1901"}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/generated_sql.sql

@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: m10
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_set_consistency
+-- intended_facet_id: low_support_extremes
+-- variant_semantic_role: rare_extreme_view
+-- template_id: tpl_m4_quantile_tail_slice
+-- query_record_id: v2q_m10_0d249ba089be7dcd
+-- problem_id: v2p_m10_4b48a03a08ad015e
+-- realization_mode: agent
+-- source_kind: agent
+WITH "buckets" AS (
+  SELECT
+    "px_height",
+    NTILE(10) OVER (ORDER BY CAST("px_height" AS REAL) DESC) AS "tail_bucket"
+  FROM "m10"
+  WHERE "px_height" IS NOT NULL
+)
+SELECT "px_height"
+FROM "buckets"
+WHERE "tail_bucket" = 1
+ORDER BY CAST("px_height" AS REAL) DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/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_quantile_tail_slice\nWITH \"buckets\" AS (\n  SELECT\n    \"px_height\",\n    NTILE(10) OVER (ORDER BY CAST(\"px_height\" AS REAL) DESC) AS \"tail_bucket\"\n  FROM \"m10\"\n  WHERE \"px_height\" IS NOT NULL\n)\nSELECT \"px_height\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY CAST(\"px_height\" AS REAL) DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n  SELECT\\n    \\\"px_height\\\",\\n    NTILE(10) OVER (ORDER BY CAST(\\\"px_height\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n  FROM \\\"m10\\\"\\n  WHERE \\\"px_height\\\" IS NOT NULL\\n)\\nSELECT \\\"px_height\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"px_height\\\" AS REAL) DESC;\", \"columns\": [\"px_height\"], \"rows\": [{\"px_height\": \"1960\"}, {\"px_height\": \"1949\"}, {\"px_height\": \"1920\"}, {\"px_height\": \"1914\"}, {\"px_height\": \"1901\"}, {\"px_height\": \"1899\"}, {\"px_height\": \"1895\"}, {\"px_height\": \"1878\"}, {\"px_height\": \"1874\"}, {\"px_height\": \"1869\"}, {\"px_height\": \"1858\"}, {\"px_height\": \"1852\"}, {\"px_height\": \"1842\"}, {\"px_height\": \"1836\"}, {\"px_height\": \"1830\"}, {\"px_height\": \"1826\"}, {\"px_height\": \"1802\"}, {\"px_height\": \"1801\"}, {\"px_height\": \"1795\"}, {\"px_height\": \"1792\"}, {\"px_height\": \"1791\"}, {\"px_height\": \"1791\"}, {\"px_height\": \"1790\"}, {\"px_height\": \"1789\"}, {\"px_height\": \"1770\"}, {\"px_height\": \"1765\"}, {\"px_height\": \"1750\"}, {\"px_height\": \"1749\"}, {\"px_height\": \"1749\"}, {\"px_height\": \"1738\"}, {\"px_height\": \"1734\"}, {\"px_height\": \"1728\"}, {\"px_height\": \"1725\"}, {\"px_height\": \"1715\"}, {\"px_height\": \"1713\"}, {\"px_height\": \"1709\"}, {\"px_height\": \"1706\"}, {\"px_height\": \"1703\"}, {\"px_height\": \"1699\"}, {\"px_height\": \"1698\"}, {\"px_height\": \"1698\"}, {\"px_height\": \"1698\"}, {\"px_height\": \"1694\"}, {\"px_height\": \"1693\"}, {\"px_height\": \"1692\"}, {\"px_height\": \"1686\"}, {\"px_height\": \"1684\"}, {\"px_height\": \"1673\"}, {\"px_height\": \"1661\"}, {\"px_height\": \"1658\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 3.15}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T15:43:48.275198+00:00",
+  "ended_at": "2026-05-19T15:44:07.399153+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_0d249ba089be7dcd",
+    "problem_id": "v2p_m10_4b48a03a08ad015e",
+    "dataset_id": "m10",
+    "template_id": "tpl_m4_quantile_tail_slice",
+    "template_name": "Quantile Tail Slice",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "rare_extreme_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=px_height.",
+    "bindings": {
+      "measure_col": "px_height",
+      "top_k": 13,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 947.25,
+      "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": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "WITH buckets AS (\n    SELECT {measure_col},\n           NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n    FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/1",
+      "binding_index=63"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 6,
+    "problem_index_within_template": 4,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "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_b/m10/sql/v2q_m10_0d249ba089be7dcd.sql",
+  "usage_summary": {
+    "dataset_id": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_0d249ba089be7dcd",
+    "api_calls": 0,
+    "input_tokens": 15270,
+    "cached_input_tokens": 14720,
+    "output_tokens": 557,
+    "total_tokens": 15827,
+    "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": 19116.23,
+    "sql_execution_elapsed_ms_total": 3.15,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:44:07.394651+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": 19116.23, "started_at": "2026-05-19T15:43:48.277332+00:00", "ended_at": "2026-05-19T15:44:07.393602+00:00", "prompt_metrics": {"chars": 10684, "bytes_utf8": 10684, "lines": 346, "estimated_tokens": null}, "response_metrics": {"chars": 583, "bytes_utf8": 583, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15270, "cached_input_tokens": 14720, "output_tokens": 557, "reasoning_output_tokens": 390}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n  SELECT\\n    \\\"px_height\\\",\\n    NTILE(10) OVER (ORDER BY CAST(\\\"px_height\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n  FROM \\\"m10\\\"\\n  WHERE \\\"px_height\\\" IS NOT NULL\\n)\\nSELECT \\\"px_height\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"px_height\\\" AS REAL) DESC;\",\"notes\":\"Uses the planned Quantile Tail Slice template with measure_col bound to \\\"px_height\\\" and num_tiles=10. \\\"px_height\\\" is cast to REAL for correct numeric tail bucketing and ordering because the schema stores it as TEXT.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "m10",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_m10_0d249ba089be7dcd",
+  "api_calls": 0,
+  "input_tokens": 15270,
+  "cached_input_tokens": 14720,
+  "output_tokens": 557,
+  "total_tokens": 15827,
+  "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": 19116.23,
+  "sql_execution_elapsed_ms_total": 3.15,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_0d249ba089be7dcd/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10e58905a124d212/cli/conversation.jsonl

@@ -0,0 +1,2 @@
+{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10924, "bytes_utf8": 10924, "lines": 350, "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": 672, "bytes_utf8": 672, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15338, "cached_input_tokens": 12032, "output_tokens": 612, "reasoning_output_tokens": 420}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10e58905a124d212/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": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_10e58905a124d212",
+    "api_calls": 0,
+    "input_tokens": 15338,
+    "cached_input_tokens": 12032,
+    "output_tokens": 612,
+    "total_tokens": 15950,
+    "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": 12757.29,
+    "sql_execution_elapsed_ms_total": 6.0,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10e58905a124d212/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10e58905a124d212/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": "2026-05-19T15:37:46.363568+00:00",
+  "ended_at": "2026-05-19T15:37:59.120895+00:00",
+  "elapsed_ms": 12757.29,
+  "prompt_metrics": {
+    "chars": 10924,
+    "bytes_utf8": 10924,
+    "lines": 350,
+    "estimated_tokens": null
+  },
+  "stdout_metrics": {
+    "chars": 1059,
+    "bytes_utf8": 1059,
+    "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": 672,
+      "bytes_utf8": 672,
+      "lines": 1,
+      "estimated_tokens": null
+    },
+    "usage": {
+      "input_tokens": 15338,
+      "cached_input_tokens": 12032,
+      "output_tokens": 612,
+      "reasoning_output_tokens": 420
+    }
+  },
+  "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/m10/artifacts/v2q_m10_10e58905a124d212/cli/sql_prompt_attempt_1.txt

@@ -0,0 +1,350 @@
+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: m10
+- dataset_name: Mobile Price Classification
+- table_name: m10
+- table_layout: single-table dataset (do not assume joins).
+- row_semantics: One row is one tabular observation with 20 feature columns and target `int_memory`.
+- task_type: regression
+- target_column: int_memory
+- main_row_count: 2000
+- important_fields:
+- battery_power: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for battery power.
+- blue: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for blue.
+- clock_speed: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for clock speed.
+- dual_sim: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for dual sim.
+- fc: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for fc.
+- four_g: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for four g.
+- int_memory: role=target, type=numeric_target. tags=['condition_candidate', 'target_candidate'] desc=Target field for int memory.
+- m_dep: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for m dep.
+- mobile_wt: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for mobile wt.
+- n_cores: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for n cores.
+- pc: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for pc.
+- px_height: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for px height.
+- px_width: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for px width.
+- ram: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for ram.
+- sc_h: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for sc h.
+- sc_w: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for sc w.
+- talk_time: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for talk time.
+- three_g: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for three g.
+- touch_screen: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for touch screen.
+- wifi: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for wifi.
+- price_range: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for price range.
+- useful_field_combinations: [['blue', 'clock_speed', 'int_memory'], ['blue', 'battery_power', 'int_memory'], ['battery_power', 'blue', 'int_memory']]
+- fields_requiring_caution: ['int_memory', 'battery_power', 'mobile_wt', 'px_height']
+- source_url: https://www.kaggle.com/datasets/iabhishekofficial/mobile-price-classification
+
+SQLite schema snapshot:
+{
+  "table_name": "m10",
+  "quoted_table_name": "\"m10\"",
+  "row_count": 2000,
+  "columns": [
+    {
+      "name": "battery_power",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "blue",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "clock_speed",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "dual_sim",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "fc",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "four_g",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "int_memory",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "m_dep",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "mobile_wt",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "n_cores",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "pc",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "px_height",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "px_width",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "ram",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "sc_h",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "sc_w",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "talk_time",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "three_g",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "touch_screen",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "wifi",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    },
+    {
+      "name": "price_range",
+      "type": "TEXT",
+      "notnull": false,
+      "pk": false
+    }
+  ],
+  "sample_rows": [
+    {
+      "battery_power": "842",
+      "blue": "0",
+      "clock_speed": "2.2",
+      "dual_sim": "0",
+      "fc": "1",
+      "four_g": "0",
+      "int_memory": "7",
+      "m_dep": "0.6",
+      "mobile_wt": "188",
+      "n_cores": "2",
+      "pc": "2",
+      "px_height": "20",
+      "px_width": "756",
+      "ram": "2549",
+      "sc_h": "9",
+      "sc_w": "7",
+      "talk_time": "19",
+      "three_g": "0",
+      "touch_screen": "0",
+      "wifi": "1",
+      "price_range": "1"
+    },
+    {
+      "battery_power": "1021",
+      "blue": "1",
+      "clock_speed": "0.5",
+      "dual_sim": "1",
+      "fc": "0",
+      "four_g": "1",
+      "int_memory": "53",
+      "m_dep": "0.7",
+      "mobile_wt": "136",
+      "n_cores": "3",
+      "pc": "6",
+      "px_height": "905",
+      "px_width": "1988",
+      "ram": "2631",
+      "sc_h": "17",
+      "sc_w": "3",
+      "talk_time": "7",
+      "three_g": "1",
+      "touch_screen": "1",
+      "wifi": "0",
+      "price_range": "2"
+    },
+    {
+      "battery_power": "563",
+      "blue": "1",
+      "clock_speed": "0.5",
+      "dual_sim": "1",
+      "fc": "2",
+      "four_g": "1",
+      "int_memory": "41",
+      "m_dep": "0.9",
+      "mobile_wt": "145",
+      "n_cores": "5",
+      "pc": "6",
+      "px_height": "1263",
+      "px_width": "1716",
+      "ram": "2603",
+      "sc_h": "11",
+      "sc_w": "2",
+      "talk_time": "9",
+      "three_g": "1",
+      "touch_screen": "1",
+      "wifi": "0",
+      "price_range": "2"
+    },
+    {
+      "battery_power": "615",
+      "blue": "1",
+      "clock_speed": "2.5",
+      "dual_sim": "0",
+      "fc": "0",
+      "four_g": "0",
+      "int_memory": "10",
+      "m_dep": "0.8",
+      "mobile_wt": "131",
+      "n_cores": "6",
+      "pc": "9",
+      "px_height": "1216",
+      "px_width": "1786",
+      "ram": "2769",
+      "sc_h": "16",
+      "sc_w": "8",
+      "talk_time": "11",
+      "three_g": "1",
+      "touch_screen": "0",
+      "wifi": "0",
+      "price_range": "2"
+    },
+    {
+      "battery_power": "1821",
+      "blue": "1",
+      "clock_speed": "1.2",
+      "dual_sim": "0",
+      "fc": "13",
+      "four_g": "1",
+      "int_memory": "44",
+      "m_dep": "0.6",
+      "mobile_wt": "141",
+      "n_cores": "2",
+      "pc": "14",
+      "px_height": "1208",
+      "px_width": "1212",
+      "ram": "1411",
+      "sc_h": "8",
+      "sc_w": "2",
+      "talk_time": "15",
+      "three_g": "1",
+      "touch_screen": "1",
+      "wifi": "0",
+      "price_range": "1"
+    }
+  ]
+}
+
+Shortlisted templates:
+[
+  {
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "primary_family": "conditional_dependency_structure",
+    "portability": "partial",
+    "sql_skeleton": "SELECT {group_col}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
+    "required_roles": [
+      "group_col",
+      "item_col",
+      "measure_col"
+    ]
+  }
+]
+
+Problem instance:
+{
+  "dataset_id": "m10",
+  "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=dual_sim, measure_col=mobile_wt.",
+  "planned_template_id": "tpl_tpcds_within_group_share",
+  "bindings": {
+    "group_col": "dual_sim",
+    "measure_col": "mobile_wt",
+    "item_col": "px_height",
+    "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": 170.0,
+    "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}, {item_col},\n       SUM({measure_col}) AS total_measure,\n       SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
+}
+
+Repair context:
+{}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10e58905a124d212/cli/sql_response_attempt_1.raw.txt

@@ -0,0 +1,4 @@
+{"type":"thread.started","thread_id":"019e40e2-cf8d-7bc3-87e4-e3260118116b"}
+{"type":"turn.started"}
+{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"dual_sim\\\",\\n  CAST(\\\"px_height\\\" AS INTEGER) AS \\\"px_height\\\",\\n  SUM(CAST(\\\"mobile_wt\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"mobile_wt\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"mobile_wt\\\" AS REAL))) OVER (PARTITION BY \\\"dual_sim\\\") AS share_within_group\\nFROM \\\"m10\\\"\\nGROUP BY \\\"dual_sim\\\", CAST(\\\"px_height\\\" AS INTEGER)\\nORDER BY share_within_group DESC\\nLIMIT 12;\",\"notes\":\"Applied the provided Within-Group Share of Total template with group_col=\\\"dual_sim\\\", item_col=\\\"px_height\\\", and measure_col=\\\"mobile_wt\\\". Cast text-stored numeric fields to INTEGER/REAL for SQLite aggregation semantics.\"}"}}
+{"type":"turn.completed","usage":{"input_tokens":15338,"cached_input_tokens":12032,"output_tokens":612,"reasoning_output_tokens":420}}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10e58905a124d212/cli/sql_response_attempt_1.txt

@@ -0,0 +1 @@
+{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n  \"dual_sim\",\n  CAST(\"px_height\" AS INTEGER) AS \"px_height\",\n  SUM(CAST(\"mobile_wt\" AS REAL)) AS total_measure,\n  SUM(CAST(\"mobile_wt\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"mobile_wt\" AS REAL))) OVER (PARTITION BY \"dual_sim\") AS share_within_group\nFROM \"m10\"\nGROUP BY \"dual_sim\", CAST(\"px_height\" AS INTEGER)\nORDER BY share_within_group DESC\nLIMIT 12;","notes":"Applied the provided Within-Group Share of Total template with group_col=\"dual_sim\", item_col=\"px_height\", and measure_col=\"mobile_wt\". Cast text-stored numeric fields to INTEGER/REAL for SQLite aggregation semantics."}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10ebe8da27522d81/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=n_cores, measure_col=pc.
+Result preview: [{"n_cores": "4", "total_measure": 2721}, {"n_cores": "7", "total_measure": 2583}, {"n_cores": "8", "total_measure": 2544}, {"n_cores": "1", "total_measure": 2536}, {"n_cores": "3", "total_measure": 2412}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10ebe8da27522d81/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: m10
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_rank_order
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_m10_10ebe8da27522d81
+-- problem_id: v2p_m10_f0b323e888f95185
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "n_cores", SUM(CAST("pc" AS NUMERIC)) AS "total_measure"
+FROM "m10"
+GROUP BY "n_cores"
+ORDER BY "total_measure" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10ebe8da27522d81/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_h2o_group_sum\nSELECT \"n_cores\", SUM(CAST(\"pc\" AS NUMERIC)) AS \"total_measure\"\nFROM \"m10\"\nGROUP BY \"n_cores\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"n_cores\\\", SUM(CAST(\\\"pc\\\" AS NUMERIC)) AS \\\"total_measure\\\"\\nFROM \\\"m10\\\"\\nGROUP BY \\\"n_cores\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"n_cores\", \"total_measure\"], \"rows\": [{\"n_cores\": \"4\", \"total_measure\": 2721}, {\"n_cores\": \"7\", \"total_measure\": 2583}, {\"n_cores\": \"8\", \"total_measure\": 2544}, {\"n_cores\": \"1\", \"total_measure\": 2536}, {\"n_cores\": \"3\", \"total_measure\": 2412}, {\"n_cores\": \"6\", \"total_measure\": 2365}, {\"n_cores\": \"2\", \"total_measure\": 2339}, {\"n_cores\": \"5\", \"total_measure\": 2333}], \"row_count_returned\": 8, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.41}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10ebe8da27522d81/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "m10",
+  "started_at": "2026-05-19T15:30:54.867434+00:00",
+  "ended_at": "2026-05-19T15:31:04.024129+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_m10_10ebe8da27522d81",
+    "problem_id": "v2p_m10_f0b323e888f95185",
+    "dataset_id": "m10",
+    "template_id": "tpl_h2o_group_sum",
+    "template_name": "Grouped Numeric Sum",
+    "family_id": "subgroup_structure",
+    "canonical_subitem_id": "internal_profile_stability",
+    "intended_facet_id": "subgroup_rank_order",
+    "variant_semantic_role": "collapsed_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=n_cores, measure_col=pc.",
+    "bindings": {
+      "group_col": "n_cores",
+      "measure_col": "pc",
+      "top_k": 16,
+      "top_n": 6,
+      "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": 13.0,
+      "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
+    },
+    "binding_roles": [
+      "group_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
+    "notes": [
+      "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=2/2",
+      "binding_index=6"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "problem_index_within_template": 7,
+    "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_b/m10/sql/v2q_m10_10ebe8da27522d81.sql",
+  "usage_summary": {
+    "dataset_id": "m10",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_m10_10ebe8da27522d81",
+    "api_calls": 0,
+    "input_tokens": 15216,
+    "cached_input_tokens": 12032,
+    "output_tokens": 348,
+    "total_tokens": 15564,
+    "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": 9150.86,
+    "sql_execution_elapsed_ms_total": 1.41,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10ebe8da27522d81/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/m10/artifacts/v2q_m10_10ebe8da27522d81/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:31:04.021354+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": 9150.86, "started_at": "2026-05-19T15:30:54.869575+00:00", "ended_at": "2026-05-19T15:31:04.020468+00:00", "prompt_metrics": {"chars": 10497, "bytes_utf8": 10497, "lines": 348, "estimated_tokens": null}, "response_metrics": {"chars": 350, "bytes_utf8": 350, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15216, "cached_input_tokens": 12032, "output_tokens": 348, "reasoning_output_tokens": 246}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"n_cores\\\", SUM(CAST(\\\"pc\\\" AS NUMERIC)) AS \\\"total_measure\\\"\\nFROM \\\"m10\\\"\\nGROUP BY \\\"n_cores\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the provided Grouped Numeric Sum template with group_col=\\\"n_cores\\\" and measure_col=\\\"pc\\\". CAST was added because the schema stores columns as TEXT.\"}"}