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Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/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=feature_3.
+Result preview: [{"feature_3": "255"}, {"feature_3": "255"}, {"feature_3": "255"}, {"feature_3": "255"}, {"feature_3": "255"}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/generated_sql.sql

@@ -0,0 +1,24 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n12
+-- 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_n12_0e7c9e65443e07ae
+-- problem_id: v2p_n12_577fb439b8d89529
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT
+        "feature_3",
+        CAST("feature_3" AS REAL) AS "feature_3_num",
+        NTILE(10) OVER (ORDER BY CAST("feature_3" AS REAL) DESC) AS tail_bucket
+    FROM "n12"
+)
+SELECT "feature_3"
+FROM buckets
+WHERE tail_bucket = 1
+ORDER BY "feature_3_num" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/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        \"feature_3\",\n        CAST(\"feature_3\" AS REAL) AS \"feature_3_num\",\n        NTILE(10) OVER (ORDER BY CAST(\"feature_3\" AS REAL) DESC) AS tail_bucket\n    FROM \"n12\"\n)\nSELECT \"feature_3\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY \"feature_3_num\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT\\n        \\\"feature_3\\\",\\n        CAST(\\\"feature_3\\\" AS REAL) AS \\\"feature_3_num\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"feature_3\\\" AS REAL) DESC) AS tail_bucket\\n    FROM \\\"n12\\\"\\n)\\nSELECT \\\"feature_3\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY \\\"feature_3_num\\\" DESC;\", \"columns\": [\"feature_3\"], \"rows\": [{\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}, {\"feature_3\": \"255\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 379.62}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:40:51.056538+00:00",
+  "ended_at": "2026-05-19T15:41:03.963217+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_0e7c9e65443e07ae",
+    "problem_id": "v2p_n12_577fb439b8d89529",
+    "dataset_id": "n12",
+    "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=feature_3.",
+    "bindings": {
+      "measure_col": "feature_3",
+      "top_k": 10,
+      "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": 186.0,
+      "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": [
+      "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=6",
+      "sql_variant_index=1/1",
+      "binding_index=65"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 6,
+    "problem_index_within_template": 6,
+    "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_a/n12/sql/v2q_n12_0e7c9e65443e07ae.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_0e7c9e65443e07ae",
+    "api_calls": 0,
+    "input_tokens": 13507,
+    "cached_input_tokens": 12672,
+    "output_tokens": 589,
+    "total_tokens": 14096,
+    "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": 12519.87,
+    "sql_execution_elapsed_ms_total": 379.62,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:41:03.579913+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": 12519.87, "started_at": "2026-05-19T15:40:51.059206+00:00", "ended_at": "2026-05-19T15:41:03.579102+00:00", "prompt_metrics": {"chars": 4716, "bytes_utf8": 4716, "lines": 142, "estimated_tokens": null}, "response_metrics": {"chars": 583, "bytes_utf8": 583, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13507, "cached_input_tokens": 12672, "output_tokens": 589, "reasoning_output_tokens": 424}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT\\n        \\\"feature_3\\\",\\n        CAST(\\\"feature_3\\\" AS REAL) AS \\\"feature_3_num\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"feature_3\\\" AS REAL) DESC) AS tail_bucket\\n    FROM \\\"n12\\\"\\n)\\nSELECT \\\"feature_3\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY \\\"feature_3_num\\\" DESC;\",\"notes\":\"Used the planned Quantile Tail Slice template with measure_col bound to \\\"feature_3\\\". Casted \\\"feature_3\\\" to REAL because the schema stores it as TEXT, ensuring numeric tail bucketing and ordering in SQLite.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_0e7c9e65443e07ae",
+  "api_calls": 0,
+  "input_tokens": 13507,
+  "cached_input_tokens": 12672,
+  "output_tokens": 589,
+  "total_tokens": 14096,
+  "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": 12519.87,
+  "sql_execution_elapsed_ms_total": 379.62,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0e7c9e65443e07ae/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_2.
+Result preview: [{"empirical_cdf_at_threshold": 0.3381090929865297}]

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/generated_sql.sql

@@ -0,0 +1,15 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n12
+-- 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_threshold_rarity_cdf
+-- query_record_id: v2q_n12_0fac57cb1e7c9e1b
+-- problem_id: v2p_n12_768cf57d01ef3535
+-- realization_mode: agent
+-- source_kind: agent
+SELECT AVG(CASE WHEN CAST("feature_2" AS REAL) <= 116.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold
+FROM "n12";

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/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_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"feature_2\" AS REAL) <= 116.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM \"n12\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_2\\\" AS REAL) <= 116.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n12\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.3381090929865297}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 38.27}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:55:14.563926+00:00",
+  "ended_at": "2026-05-19T15:55:25.389027+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_0fac57cb1e7c9e1b",
+    "problem_id": "v2p_n12_768cf57d01ef3535",
+    "dataset_id": "n12",
+    "template_id": "tpl_threshold_rarity_cdf",
+    "template_name": "Threshold Rarity CDF",
+    "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 Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=feature_2.",
+    "bindings": {
+      "measure_col": "feature_2",
+      "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": 116.0,
+      "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": [
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/1",
+      "binding_index=109"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 2,
+    "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_a/n12/sql/v2q_n12_0fac57cb1e7c9e1b.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_0fac57cb1e7c9e1b",
+    "api_calls": 0,
+    "input_tokens": 13443,
+    "cached_input_tokens": 12672,
+    "output_tokens": 199,
+    "total_tokens": 13642,
+    "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": 9779.47,
+    "sql_execution_elapsed_ms_total": 38.27,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:55:17.808679+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": 3241.74, "started_at": "2026-05-19T15:55:14.566160+00:00", "ended_at": "2026-05-19T15:55:17.807926+00:00", "prompt_metrics": {"chars": 4482, "bytes_utf8": 4482, "lines": 142, "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-ce2d-7372-b128-1e51defaeef5\"}\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": "2026-05-19T15:55:25.348794+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": 6537.73, "started_at": "2026-05-19T15:55:18.809934+00:00", "ended_at": "2026-05-19T15:55:25.347716+00:00", "prompt_metrics": {"chars": 4482, "bytes_utf8": 4482, "lines": 142, "estimated_tokens": null}, "response_metrics": {"chars": 381, "bytes_utf8": 381, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13443, "cached_input_tokens": 12672, "output_tokens": 199, "reasoning_output_tokens": 94}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"feature_2\\\" AS REAL) <= 116.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n12\\\";\",\"notes\":\"Used the provided Threshold Rarity CDF template with measure_col bound to feature_2 and measure_threshold fixed at 116.0. CAST to REAL is included because the schema stores feature columns as TEXT.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_0fac57cb1e7c9e1b",
+  "api_calls": 0,
+  "input_tokens": 13443,
+  "cached_input_tokens": 12672,
+  "output_tokens": 199,
+  "total_tokens": 13642,
+  "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": 9779.47,
+  "sql_execution_elapsed_ms_total": 38.27,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_0fac57cb1e7c9e1b/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_1e0398700e4c41c6/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=feature_3, measure_col=feature_3.
+Result preview: [{"feature_3": "170", "feature_1": "205", "total_measure": 119340.0, "share_within_group": 63.76021798365122}, {"feature_3": "164", "feature_1": "201", "total_measure": 116276.0, "share_within_group": 56.629392971246006}, {"feature_3": "165", "feature_1": "202", "total_measure": 69795.0, "share_within_group": 52.22222222222222}, {"feature_3": "158", "feature_1": "198", "total_measure": 172220.0, "share_within_group": 50.83955223880597}, {"feature_3": "113", "feature_1": "164", "total_measure": 104073.0, "share_within_group": 44.70873786407767}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_1e0398700e4c41c6/generated_sql.sql

@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n12
+-- 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_tpcds_within_group_share
+-- query_record_id: v2q_n12_1e0398700e4c41c6
+-- problem_id: v2p_n12_4c64c458d44d5897
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_3",
+  "feature_1",
+  SUM(CAST("feature_3" AS REAL)) AS total_measure,
+  SUM(CAST("feature_3" AS REAL)) * 100.0
+    / SUM(SUM(CAST("feature_3" AS REAL))) OVER (PARTITION BY "feature_3") AS share_within_group
+FROM "n12"
+GROUP BY "feature_3", "feature_1"
+ORDER BY share_within_group DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_1e0398700e4c41c6/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_tpcds_within_group_share\nSELECT\n  \"feature_3\",\n  \"feature_1\",\n  SUM(CAST(\"feature_3\" AS REAL)) AS total_measure,\n  SUM(CAST(\"feature_3\" AS REAL)) * 100.0\n    / SUM(SUM(CAST(\"feature_3\" AS REAL))) OVER (PARTITION BY \"feature_3\") AS share_within_group\nFROM \"n12\"\nGROUP BY \"feature_3\", \"feature_1\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_3\\\",\\n  \\\"feature_1\\\",\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"feature_3\\\" AS REAL))) OVER (PARTITION BY \\\"feature_3\\\") AS share_within_group\\nFROM \\\"n12\\\"\\nGROUP BY \\\"feature_3\\\", \\\"feature_1\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"feature_3\", \"feature_1\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"feature_3\": \"170\", \"feature_1\": \"205\", \"total_measure\": 119340.0, \"share_within_group\": 63.76021798365122}, {\"feature_3\": \"164\", \"feature_1\": \"201\", \"total_measure\": 116276.0, \"share_within_group\": 56.629392971246006}, {\"feature_3\": \"165\", \"feature_1\": \"202\", \"total_measure\": 69795.0, \"share_within_group\": 52.22222222222222}, {\"feature_3\": \"158\", \"feature_1\": \"198\", \"total_measure\": 172220.0, \"share_within_group\": 50.83955223880597}, {\"feature_3\": \"113\", \"feature_1\": \"164\", \"total_measure\": 104073.0, \"share_within_group\": 44.70873786407767}, {\"feature_3\": \"157\", \"feature_1\": \"196\", \"total_measure\": 103306.0, \"share_within_group\": 43.23258869908016}, {\"feature_3\": \"162\", \"feature_1\": \"201\", \"total_measure\": 264222.0, \"share_within_group\": 42.57374053771861}, {\"feature_3\": \"121\", \"feature_1\": \"172\", \"total_measure\": 123904.0, \"share_within_group\": 41.89852700490999}, {\"feature_3\": \"72\", \"feature_1\": \"4\", \"total_measure\": 11664.0, \"share_within_group\": 41.53846153846154}, {\"feature_3\": \"156\", \"feature_1\": \"195\", \"total_measure\": 68796.0, \"share_within_group\": 40.16393442622951}, {\"feature_3\": \"131\", \"feature_1\": \"178\", \"total_measure\": 196762.0, \"share_within_group\": 39.60970464135021}, {\"feature_3\": \"162\", \"feature_1\": \"199\", \"total_measure\": 244458.0, \"share_within_group\": 39.389193422083004}, {\"feature_3\": \"90\", \"feature_1\": \"136\", \"total_measure\": 56610.0, \"share_within_group\": 39.141257000622275}, {\"feature_3\": \"129\", \"feature_1\": \"179\", \"total_measure\": 172989.0, \"share_within_group\": 38.118249005116546}, {\"feature_3\": \"135\", \"feature_1\": \"182\", \"total_measure\": 162810.0, \"share_within_group\": 37.23371410929299}, {\"feature_3\": \"134\", \"feature_1\": \"181\", \"total_measure\": 132794.0, \"share_within_group\": 35.87979724837074}, {\"feature_3\": \"163\", \"feature_1\": \"200\", \"total_measure\": 160229.0, \"share_within_group\": 35.758457620953074}, {\"feature_3\": \"169\", \"feature_1\": \"204\", \"total_measure\": 44785.0, \"share_within_group\": 35.52278820375335}, {\"feature_3\": \"122\", \"feature_1\": \"173\", \"total_measure\": 98820.0, \"share_within_group\": 34.79381443298969}, {\"feature_3\": \"138\", \"feature_1\": \"183\", \"total_measure\": 72450.0, \"share_within_group\": 33.91472868217054}, {\"feature_3\": \"160\", \"feature_1\": \"199\", \"total_measure\": 98080.0, \"share_within_group\": 33.68131868131868}, {\"feature_3\": \"21\", \"feature_1\": \"54\", \"total_measure\": 15624.0, \"share_within_group\": 33.46828609986505}, {\"feature_3\": \"160\", \"feature_1\": \"197\", \"total_measure\": 96800.0, \"share_within_group\": 33.24175824175824}, {\"feature_3\": \"139\", \"feature_1\": \"184\", \"total_measure\": 47121.0, \"share_within_group\": 33.17025440313112}, {\"feature_3\": \"250\", \"feature_1\": \"248\", \"total_measure\": 83250.0, \"share_within_group\": 33.1013916500994}, {\"feature_3\": \"163\", \"feature_1\": \"199\", \"total_measure\": 145559.0, \"share_within_group\": 32.48453983266642}, {\"feature_3\": \"133\", \"feature_1\": \"181\", \"total_measure\": 103740.0, \"share_within_group\": 32.445923460898506}, {\"feature_3\": \"57\", \"feature_1\": \"116\", \"total_measure\": 9120.0, \"share_within_group\": 32.323232323232325}, {\"feature_3\": \"115\", \"feature_1\": \"165\", \"total_measure\": 65320.0, \"share_within_group\": 31.123287671232877}, {\"feature_3\": \"112\", \"feature_1\": \"163\", \"total_measure\": 75152.0, \"share_within_group\": 30.555555555555557}, {\"feature_3\": \"120\", \"feature_1\": \"171\", \"total_measure\": 72600.0, \"share_within_group\": 30.20469296055916}, {\"feature_3\": \"124\", \"feature_1\": \"174\", \"total_measure\": 79360.0, \"share_within_group\": 30.14601978332548}, {\"feature_3\": \"168\", \"feature_1\": \"204\", \"total_measure\": 31248.0, \"share_within_group\": 30.0}, {\"feature_3\": \"128\", \"feature_1\": \"178\", \"total_measure\": 110080.0, \"share_within_group\": 29.43189596167009}, {\"feature_3\": \"7\", \"feature_1\": \"32\", \"total_measure\": 2989.0, \"share_within_group\": 29.1866028708134}, {\"feature_3\": \"59\", \"feature_1\": \"118\", \"total_measure\": 7434.0, \"share_within_group\": 28.506787330316744}, {\"feature_3\": \"130\", \"feature_1\": \"178\", \"total_measure\": 88790.0, \"share_within_group\": 28.50584307178631}, {\"feature_3\": \"155\", \"feature_1\": \"194\", \"total_measure\": 39060.0, \"share_within_group\": 28.47457627118644}, {\"feature_3\": \"89\", \"feature_1\": \"138\", \"total_measure\": 36846.0, \"share_within_group\": 28.45360824742268}, {\"feature_3\": \"125\", \"feature_1\": \"175\", \"total_measure\": 90500.0, \"share_within_group\": 28.248146703082327}, {\"feature_3\": \"159\", \"feature_1\": \"198\", \"total_measure\": 54696.0, \"share_within_group\": 28.01302931596091}, {\"feature_3\": \"8\", \"feature_1\": \"35\", \"total_measure\": 2928.0, \"share_within_group\": 27.790432801822323}, {\"feature_3\": \"55\", \"feature_1\": \"114\", \"total_measure\": 6050.0, \"share_within_group\": 27.77777777777778}, {\"feature_3\": \"81\", \"feature_1\": \"140\", \"total_measure\": 9396.0, \"share_within_group\": 27.684964200477328}, {\"feature_3\": \"140\", \"feature_1\": \"185\", \"total_measure\": 39340.0, \"share_within_group\": 27.30806608357629}, {\"feature_3\": \"132\", \"feature_1\": \"180\", \"total_measure\": 135036.0, \"share_within_group\": 27.229172211871173}, {\"feature_3\": \"117\", \"feature_1\": \"165\", \"total_measure\": 28899.0, \"share_within_group\": 26.789587852494577}, {\"feature_3\": \"114\", \"feature_1\": \"164\", \"total_measure\": 88578.0, \"share_within_group\": 26.728586171310628}, {\"feature_3\": \"126\", \"feature_1\": \"176\", \"total_measure\": 88200.0, \"share_within_group\": 26.41509433962264}, {\"feature_3\": \"60\", \"feature_1\": \"119\", \"total_measure\": 7080.0, \"share_within_group\": 26.106194690265486}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 246.22}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_1e0398700e4c41c6/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:33:57.204130+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": 15421.91, "started_at": "2026-05-19T15:33:41.781346+00:00", "ended_at": "2026-05-19T15:33:57.203288+00:00", "prompt_metrics": {"chars": 4959, "bytes_utf8": 4959, "lines": 146, "estimated_tokens": null}, "response_metrics": {"chars": 614, "bytes_utf8": 614, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13576, "cached_input_tokens": 12672, "output_tokens": 704, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"feature_3\\\",\\n  \\\"feature_1\\\",\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) * 100.0\\n    / SUM(SUM(CAST(\\\"feature_3\\\" AS REAL))) OVER (PARTITION BY \\\"feature_3\\\") AS share_within_group\\nFROM \\\"n12\\\"\\nGROUP BY \\\"feature_3\\\", \\\"feature_1\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the planned Within-Group Share of Total template with group_col=\\\"feature_3\\\", item_col=\\\"feature_1\\\", and measure_col=\\\"feature_3\\\". Casted \\\"feature_3\\\" to REAL because the schema stores it as TEXT in SQLite.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=target, measure_col=feature_2.
+Result preview: [{"target": "2", "group_value": 25015862.0}, {"target": "1", "group_value": 7455986.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/generated_sql.sql

@@ -0,0 +1,27 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n12
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n12_323a84fcf8248e82
+-- problem_id: v2p_n12_aa5e442557cf938f
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT "target", SUM(CAST("feature_2" AS REAL)) AS "group_value"
+  FROM "n12"
+  GROUP BY "target"
+),
+"total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT g."target", g."group_value"
+FROM "grouped" AS g
+CROSS JOIN "total" AS t
+WHERE g."group_value" > t."total_value" * 0.1
+ORDER BY g."group_value" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/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_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n  SELECT \"target\", SUM(CAST(\"feature_2\" AS REAL)) AS \"group_value\"\n  FROM \"n12\"\n  GROUP BY \"target\"\n),\n\"total\" AS (\n  SELECT SUM(\"group_value\") AS \"total_value\"\n  FROM \"grouped\"\n)\nSELECT g.\"target\", g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n  SELECT \\\"target\\\", SUM(CAST(\\\"feature_2\\\" AS REAL)) AS \\\"group_value\\\"\\n  FROM \\\"n12\\\"\\n  GROUP BY \\\"target\\\"\\n),\\n\\\"total\\\" AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"target\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"target\", \"group_value\"], \"rows\": [{\"target\": \"2\", \"group_value\": 25015862.0}, {\"target\": \"1\", \"group_value\": 7455986.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 83.12}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:44:35.912201+00:00",
+  "ended_at": "2026-05-19T15:44:54.581667+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_323a84fcf8248e82",
+    "problem_id": "v2p_n12_aa5e442557cf938f",
+    "dataset_id": "n12",
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "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 Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=target, measure_col=feature_2.",
+    "bindings": {
+      "group_col": "target",
+      "measure_col": "feature_2",
+      "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": 116.0,
+      "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": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=8",
+      "sql_variant_index=1/2",
+      "binding_index=79"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 8,
+    "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/n12/sql/v2q_n12_323a84fcf8248e82.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_323a84fcf8248e82",
+    "api_calls": 0,
+    "input_tokens": 13590,
+    "cached_input_tokens": 12032,
+    "output_tokens": 704,
+    "total_tokens": 14294,
+    "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": 18580.42,
+    "sql_execution_elapsed_ms_total": 83.12,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:44:54.496599+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": 18580.42, "started_at": "2026-05-19T15:44:35.915202+00:00", "ended_at": "2026-05-19T15:44:54.495658+00:00", "prompt_metrics": {"chars": 5097, "bytes_utf8": 5097, "lines": 144, "estimated_tokens": null}, "response_metrics": {"chars": 626, "bytes_utf8": 626, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13590, "cached_input_tokens": 12032, "output_tokens": 704, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n  SELECT \\\"target\\\", SUM(CAST(\\\"feature_2\\\" AS REAL)) AS \\\"group_value\\\"\\n  FROM \\\"n12\\\"\\n  GROUP BY \\\"target\\\"\\n),\\n\\\"total\\\" AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"target\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Used the provided template with group_col=\\\"target\\\" and measure_col=\\\"feature_2\\\"; cast \\\"feature_2\\\" from TEXT to REAL for SQLite numeric aggregation.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_323a84fcf8248e82",
+  "api_calls": 0,
+  "input_tokens": 13590,
+  "cached_input_tokens": 12032,
+  "output_tokens": 704,
+  "total_tokens": 14294,
+  "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": 18580.42,
+  "sql_execution_elapsed_ms_total": 83.12,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_323a84fcf8248e82/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_42fabdd853eeaef6/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:43:26.270479+00:00",
+  "ended_at": "2026-05-19T15:43:40.738011+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_42fabdd853eeaef6",
+    "problem_id": "v2p_n12_6e19fb64c65c1179",
+    "dataset_id": "n12",
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "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 Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_1, measure_col=feature_2.",
+    "bindings": {
+      "group_col": "feature_1",
+      "measure_col": "feature_2",
+      "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": 104.84,
+      "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": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=2/2",
+      "binding_index=76"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 5,
+    "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/n12/sql/v2q_n12_42fabdd853eeaef6.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_42fabdd853eeaef6",
+    "api_calls": 0,
+    "input_tokens": 13594,
+    "cached_input_tokens": 12672,
+    "output_tokens": 686,
+    "total_tokens": 14280,
+    "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": 14336.78,
+    "sql_execution_elapsed_ms_total": 124.87,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_42fabdd853eeaef6/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_42fabdd853eeaef6/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_42fabdd853eeaef6",
+  "api_calls": 0,
+  "input_tokens": 13594,
+  "cached_input_tokens": 12672,
+  "output_tokens": 686,
+  "total_tokens": 14280,
+  "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": 14336.78,
+  "sql_execution_elapsed_ms_total": 124.87,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_42fabdd853eeaef6/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=target, condition_col=target.
+Result preview: [{"target": "1", "condition_rate": 1.0}, {"target": "2", "condition_rate": 0.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/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: n12
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_m4_group_condition_rate
+-- query_record_id: v2q_n12_4b4368e8d034fea4
+-- problem_id: v2p_n12_51cd0ab1976a73b1
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "target",
+       AVG(CASE WHEN "target" = '1' THEN 1 ELSE 0 END) AS condition_rate
+FROM "n12"
+GROUP BY "target"
+ORDER BY condition_rate DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/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_m4_group_condition_rate\nSELECT \"target\",\n       AVG(CASE WHEN \"target\" = '1' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"n12\"\nGROUP BY \"target\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"target\\\",\\n       AVG(CASE WHEN \\\"target\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n12\\\"\\nGROUP BY \\\"target\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"target\", \"condition_rate\"], \"rows\": [{\"target\": \"1\", \"condition_rate\": 1.0}, {\"target\": \"2\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 73.94}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/run_manifest.json

@@ -0,0 +1,92 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:53:34.487781+00:00",
+  "ended_at": "2026-05-19T15:53:48.407773+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_4b4368e8d034fea4",
+    "problem_id": "v2p_n12_51cd0ab1976a73b1",
+    "dataset_id": "n12",
+    "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": "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 direction_consistency with semantic role focused_target_view. Focus on group_col=target, condition_col=target.",
+    "bindings": {
+      "group_col": "target",
+      "condition_col": "target",
+      "condition_value": "1",
+      "positive_value": "1",
+      "negative_value": "2",
+      "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": 115.0,
+      "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=conditional_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=4",
+      "sql_variant_index=1/2",
+      "binding_index=99"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "problem_index_within_template": 4,
+    "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/n12/sql/v2q_n12_4b4368e8d034fea4.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_4b4368e8d034fea4",
+    "api_calls": 0,
+    "input_tokens": 13509,
+    "cached_input_tokens": 12672,
+    "output_tokens": 431,
+    "total_tokens": 13940,
+    "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": 12837.91,
+    "sql_execution_elapsed_ms_total": 73.94,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:53:37.147120+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": 2655.62, "started_at": "2026-05-19T15:53:34.490708+00:00", "ended_at": "2026-05-19T15:53:37.146356+00:00", "prompt_metrics": {"chars": 4772, "bytes_utf8": 4772, "lines": 147, "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\":\"019e40f1-4724-7c41-8a71-603f8f24a4bb\"}\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": "2026-05-19T15:53:48.331430+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": 10182.29, "started_at": "2026-05-19T15:53:38.148336+00:00", "ended_at": "2026-05-19T15:53:48.330674+00:00", "prompt_metrics": {"chars": 4772, "bytes_utf8": 4772, "lines": 147, "estimated_tokens": null}, "response_metrics": {"chars": 470, "bytes_utf8": 470, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13509, "cached_input_tokens": 12672, "output_tokens": 431, "reasoning_output_tokens": 304}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"target\\\",\\n       AVG(CASE WHEN \\\"target\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n12\\\"\\nGROUP BY \\\"target\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Uses the Grouped Condition Rate template with group_col=\\\"target\\\" and condition_col=\\\"target\\\". Because the grouping column and condition column are the same, the resulting rate is 1.0 for rows where target='1' and 0.0 for other target groups.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_4b4368e8d034fea4",
+  "api_calls": 0,
+  "input_tokens": 13509,
+  "cached_input_tokens": 12672,
+  "output_tokens": 431,
+  "total_tokens": 13940,
+  "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": 12837.91,
+  "sql_execution_elapsed_ms_total": 73.94,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_4b4368e8d034fea4/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/final_answer.txt

@@ -0,0 +1 @@
+No rows were returned for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_2, measure_col=feature_3.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/generated_sql.sql

@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n12
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_n12_70c6ebd1768f6430
+-- problem_id: v2p_n12_6fb93a004868f54a
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "feature_2", SUM(CAST("feature_3" AS REAL)) AS group_value
+    FROM "n12"
+    GROUP BY "feature_2"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."feature_2", g.group_value
+FROM grouped AS g
+CROSS JOIN total AS t
+WHERE g.group_value > t.total_value * 0.1
+ORDER BY g.group_value DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/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_tpch_relative_total_threshold\nWITH grouped AS (\n    SELECT \"feature_2\", SUM(CAST(\"feature_3\" AS REAL)) AS group_value\n    FROM \"n12\"\n    GROUP BY \"feature_2\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"feature_2\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_2\\\", SUM(CAST(\\\"feature_3\\\" AS REAL)) AS group_value\\n    FROM \\\"n12\\\"\\n    GROUP BY \\\"feature_2\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_2\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\", \"columns\": [\"feature_2\", \"group_value\"], \"rows\": [], \"row_count_returned\": 0, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 127.59}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:43:40.738554+00:00",
+  "ended_at": "2026-05-19T15:43:56.461609+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_70c6ebd1768f6430",
+    "problem_id": "v2p_n12_6fb93a004868f54a",
+    "dataset_id": "n12",
+    "template_id": "tpl_tpch_relative_total_threshold",
+    "template_name": "Relative-to-Total Extreme Threshold",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_mass_similarity",
+    "intended_facet_id": "tail_ranked_signal",
+    "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 Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=feature_2, measure_col=feature_3.",
+    "bindings": {
+      "group_col": "feature_2",
+      "measure_col": "feature_3",
+      "top_k": 12,
+      "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": 186.0,
+      "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": "WITH grouped AS (\n    SELECT {group_col}, SUM({measure_col}) AS group_value\n    FROM {table}\n    GROUP BY {group_col}\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
+    "notes": [
+      "default_facets=tail_ranked_signal",
+      "template_selection_mode=rule",
+      "problem_index_within_template=6",
+      "sql_variant_index=1/2",
+      "binding_index=77"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "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/n12/sql/v2q_n12_70c6ebd1768f6430.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_70c6ebd1768f6430",
+    "api_calls": 0,
+    "input_tokens": 13594,
+    "cached_input_tokens": 12032,
+    "output_tokens": 435,
+    "total_tokens": 14029,
+    "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": 15589.43,
+    "sql_execution_elapsed_ms_total": 127.59,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:43:56.331939+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": 15589.43, "started_at": "2026-05-19T15:43:40.741508+00:00", "ended_at": "2026-05-19T15:43:56.330967+00:00", "prompt_metrics": {"chars": 5103, "bytes_utf8": 5103, "lines": 144, "estimated_tokens": null}, "response_metrics": {"chars": 635, "bytes_utf8": 635, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13594, "cached_input_tokens": 12032, "output_tokens": 435, "reasoning_output_tokens": 261}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"feature_2\\\", SUM(CAST(\\\"feature_3\\\" AS REAL)) AS group_value\\n    FROM \\\"n12\\\"\\n    GROUP BY \\\"feature_2\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"feature_2\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the provided Relative-to-Total Extreme Threshold template with group_col=\\\"feature_2\\\" and measure_col=\\\"feature_3\\\". Cast \\\"feature_3\\\" from TEXT to REAL for SQLite-safe aggregation.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_70c6ebd1768f6430",
+  "api_calls": 0,
+  "input_tokens": 13594,
+  "cached_input_tokens": 12032,
+  "output_tokens": 435,
+  "total_tokens": 14029,
+  "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": 15589.43,
+  "sql_execution_elapsed_ms_total": 127.59,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_70c6ebd1768f6430/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/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=feature_2, measure_col=feature_3.
+Result preview: [{"feature_2": "178", "total_measure": 692715.0}, {"feature_2": "179", "total_measure": 655339.0}, {"feature_2": "177", "total_measure": 600046.0}, {"feature_2": "175", "total_measure": 576115.0}, {"feature_2": "197", "total_measure": 569529.0}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/generated_sql.sql

@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n12
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n12_a89cf6e292ba8ffd
+-- problem_id: v2p_n12_348a9656f2624e7b
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_2",
+  SUM(CAST("feature_3" AS REAL)) AS "total_measure"
+FROM "n12"
+GROUP BY "feature_2"
+ORDER BY "total_measure" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/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  \"feature_2\",\n  SUM(CAST(\"feature_3\" AS REAL)) AS \"total_measure\"\nFROM \"n12\"\nGROUP BY \"feature_2\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT\\n  \\\"feature_2\\\",\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n12\\\"\\nGROUP BY \\\"feature_2\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"feature_2\", \"total_measure\"], \"rows\": [{\"feature_2\": \"178\", \"total_measure\": 692715.0}, {\"feature_2\": \"179\", \"total_measure\": 655339.0}, {\"feature_2\": \"177\", \"total_measure\": 600046.0}, {\"feature_2\": \"175\", \"total_measure\": 576115.0}, {\"feature_2\": \"197\", \"total_measure\": 569529.0}, {\"feature_2\": \"163\", \"total_measure\": 549769.0}, {\"feature_2\": \"176\", \"total_measure\": 543726.0}, {\"feature_2\": \"198\", \"total_measure\": 510951.0}, {\"feature_2\": \"162\", \"total_measure\": 475823.0}, {\"feature_2\": \"180\", \"total_measure\": 440083.0}, {\"feature_2\": \"172\", \"total_measure\": 432501.0}, {\"feature_2\": \"174\", \"total_measure\": 421025.0}, {\"feature_2\": \"161\", \"total_measure\": 399927.0}, {\"feature_2\": \"170\", \"total_measure\": 393648.0}, {\"feature_2\": \"195\", \"total_measure\": 388576.0}, {\"feature_2\": \"200\", \"total_measure\": 386254.0}, {\"feature_2\": \"164\", \"total_measure\": 384006.0}, {\"feature_2\": \"171\", \"total_measure\": 380711.0}, {\"feature_2\": \"181\", \"total_measure\": 375722.0}, {\"feature_2\": \"165\", \"total_measure\": 350700.0}, {\"feature_2\": \"173\", \"total_measure\": 343893.0}, {\"feature_2\": \"169\", \"total_measure\": 339961.0}, {\"feature_2\": \"160\", \"total_measure\": 335373.0}, {\"feature_2\": \"183\", \"total_measure\": 330460.0}, {\"feature_2\": \"182\", \"total_measure\": 316756.0}, {\"feature_2\": \"168\", \"total_measure\": 297593.0}, {\"feature_2\": \"184\", \"total_measure\": 296551.0}, {\"feature_2\": \"166\", \"total_measure\": 295186.0}, {\"feature_2\": \"194\", \"total_measure\": 293863.0}, {\"feature_2\": \"255\", \"total_measure\": 289323.0}, {\"feature_2\": \"186\", \"total_measure\": 284790.0}, {\"feature_2\": \"190\", \"total_measure\": 283714.0}, {\"feature_2\": \"0\", \"total_measure\": 282918.0}, {\"feature_2\": \"185\", \"total_measure\": 280193.0}, {\"feature_2\": \"139\", \"total_measure\": 276296.0}, {\"feature_2\": \"159\", \"total_measure\": 266577.0}, {\"feature_2\": \"192\", \"total_measure\": 266487.0}, {\"feature_2\": \"193\", \"total_measure\": 262577.0}, {\"feature_2\": \"188\", \"total_measure\": 258036.0}, {\"feature_2\": \"187\", \"total_measure\": 257660.0}, {\"feature_2\": \"189\", \"total_measure\": 253307.0}, {\"feature_2\": \"196\", \"total_measure\": 250437.0}, {\"feature_2\": \"167\", \"total_measure\": 243004.0}, {\"feature_2\": \"158\", \"total_measure\": 239418.0}, {\"feature_2\": \"191\", \"total_measure\": 232114.0}, {\"feature_2\": \"157\", \"total_measure\": 227726.0}, {\"feature_2\": \"199\", \"total_measure\": 226791.0}, {\"feature_2\": \"154\", \"total_measure\": 219271.0}, {\"feature_2\": \"140\", \"total_measure\": 217349.0}, {\"feature_2\": \"152\", \"total_measure\": 216519.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 116.6}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:30:14.836299+00:00",
+  "ended_at": "2026-05-19T15:30:29.044935+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_a89cf6e292ba8ffd",
+    "problem_id": "v2p_n12_348a9656f2624e7b",
+    "dataset_id": "n12",
+    "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_conditional_contrast",
+    "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=feature_2, measure_col=feature_3.",
+    "bindings": {
+      "group_col": "feature_2",
+      "measure_col": "feature_3",
+      "top_k": 10,
+      "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": 186.0,
+      "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=6",
+      "sql_variant_index=1/2",
+      "binding_index=5"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "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/n12/sql/v2q_n12_a89cf6e292ba8ffd.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_a89cf6e292ba8ffd",
+    "api_calls": 0,
+    "input_tokens": 13456,
+    "cached_input_tokens": 12032,
+    "output_tokens": 477,
+    "total_tokens": 13933,
+    "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": 14084.75,
+    "sql_execution_elapsed_ms_total": 116.6,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:30:28.925812+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": 14084.75, "started_at": "2026-05-19T15:30:14.840007+00:00", "ended_at": "2026-05-19T15:30:28.924801+00:00", "prompt_metrics": {"chars": 4547, "bytes_utf8": 4547, "lines": 144, "estimated_tokens": null}, "response_metrics": {"chars": 411, "bytes_utf8": 411, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13456, "cached_input_tokens": 12032, "output_tokens": 477, "reasoning_output_tokens": 362}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT\\n  \\\"feature_2\\\",\\n  SUM(CAST(\\\"feature_3\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n12\\\"\\nGROUP BY \\\"feature_2\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied the grouped numeric sum template with \\\"feature_2\\\" as the grouping column and \\\"feature_3\\\" as the summed measure. CAST is used because the schema stores these numeric fields as TEXT in SQLite.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_a89cf6e292ba8ffd",
+  "api_calls": 0,
+  "input_tokens": 13456,
+  "cached_input_tokens": 12032,
+  "output_tokens": 477,
+  "total_tokens": 13933,
+  "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": 14084.75,
+  "sql_execution_elapsed_ms_total": 116.6,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_a89cf6e292ba8ffd/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=feature_2, measure_col=feature_2.
+Result preview: [{"feature_2": "255", "avg_measure": 255.0}, {"feature_2": "254", "avg_measure": 254.0}, {"feature_2": "253", "avg_measure": 253.0}, {"feature_2": "252", "avg_measure": 252.0}, {"feature_2": "251", "avg_measure": 251.0}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/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: n12
+-- family_id: conditional_dependency_structure
+-- canonical_subitem_id: direction_consistency
+-- intended_facet_id: conditional_rate_shift
+-- variant_semantic_role: filtered_stable_view
+-- template_id: tpl_m4_window_partition_avg
+-- query_record_id: v2q_n12_b570ed79a8fcba38
+-- problem_id: v2p_n12_c64adeef051a1f27
+-- realization_mode: agent
+-- source_kind: agent
+SELECT DISTINCT "feature_2",
+       AVG(CAST("feature_2" AS REAL)) OVER (PARTITION BY "feature_2") AS avg_measure
+FROM "n12"
+WHERE "feature_2" IS NOT NULL
+ORDER BY avg_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/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_m4_window_partition_avg\nSELECT DISTINCT \"feature_2\",\n       AVG(CAST(\"feature_2\" AS REAL)) OVER (PARTITION BY \"feature_2\") AS avg_measure\nFROM \"n12\"\nWHERE \"feature_2\" IS NOT NULL\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"feature_2\\\",\\n       AVG(CAST(\\\"feature_2\\\" AS REAL)) OVER (PARTITION BY \\\"feature_2\\\") AS avg_measure\\nFROM \\\"n12\\\"\\nWHERE \\\"feature_2\\\" IS NOT NULL\\nORDER BY avg_measure DESC;\", \"columns\": [\"feature_2\", \"avg_measure\"], \"rows\": [{\"feature_2\": \"255\", \"avg_measure\": 255.0}, {\"feature_2\": \"254\", \"avg_measure\": 254.0}, {\"feature_2\": \"253\", \"avg_measure\": 253.0}, {\"feature_2\": \"252\", \"avg_measure\": 252.0}, {\"feature_2\": \"251\", \"avg_measure\": 251.0}, {\"feature_2\": \"250\", \"avg_measure\": 250.0}, {\"feature_2\": \"249\", \"avg_measure\": 249.0}, {\"feature_2\": \"248\", \"avg_measure\": 248.0}, {\"feature_2\": \"247\", \"avg_measure\": 247.0}, {\"feature_2\": \"246\", \"avg_measure\": 246.0}, {\"feature_2\": \"245\", \"avg_measure\": 245.0}, {\"feature_2\": \"244\", \"avg_measure\": 244.0}, {\"feature_2\": \"243\", \"avg_measure\": 243.0}, {\"feature_2\": \"242\", \"avg_measure\": 242.0}, {\"feature_2\": \"241\", \"avg_measure\": 241.0}, {\"feature_2\": \"240\", \"avg_measure\": 240.0}, {\"feature_2\": \"239\", \"avg_measure\": 239.0}, {\"feature_2\": \"238\", \"avg_measure\": 238.0}, {\"feature_2\": \"237\", \"avg_measure\": 237.0}, {\"feature_2\": \"236\", \"avg_measure\": 236.0}, {\"feature_2\": \"235\", \"avg_measure\": 235.0}, {\"feature_2\": \"234\", \"avg_measure\": 234.0}, {\"feature_2\": \"233\", \"avg_measure\": 233.0}, {\"feature_2\": \"232\", \"avg_measure\": 232.0}, {\"feature_2\": \"231\", \"avg_measure\": 231.0}, {\"feature_2\": \"230\", \"avg_measure\": 230.0}, {\"feature_2\": \"229\", \"avg_measure\": 229.0}, {\"feature_2\": \"228\", \"avg_measure\": 228.0}, {\"feature_2\": \"227\", \"avg_measure\": 227.0}, {\"feature_2\": \"226\", \"avg_measure\": 226.0}, {\"feature_2\": \"225\", \"avg_measure\": 225.0}, {\"feature_2\": \"224\", \"avg_measure\": 224.0}, {\"feature_2\": \"223\", \"avg_measure\": 223.0}, {\"feature_2\": \"222\", \"avg_measure\": 222.0}, {\"feature_2\": \"221\", \"avg_measure\": 221.0}, {\"feature_2\": \"220\", \"avg_measure\": 220.0}, {\"feature_2\": \"219\", \"avg_measure\": 219.0}, {\"feature_2\": \"218\", \"avg_measure\": 218.0}, {\"feature_2\": \"217\", \"avg_measure\": 217.0}, {\"feature_2\": \"216\", \"avg_measure\": 216.0}, {\"feature_2\": \"215\", \"avg_measure\": 215.0}, {\"feature_2\": \"214\", \"avg_measure\": 214.0}, {\"feature_2\": \"213\", \"avg_measure\": 213.0}, {\"feature_2\": \"212\", \"avg_measure\": 212.0}, {\"feature_2\": \"211\", \"avg_measure\": 211.0}, {\"feature_2\": \"210\", \"avg_measure\": 210.0}, {\"feature_2\": \"209\", \"avg_measure\": 209.0}, {\"feature_2\": \"208\", \"avg_measure\": 208.0}, {\"feature_2\": \"207\", \"avg_measure\": 207.0}, {\"feature_2\": \"206\", \"avg_measure\": 206.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 381.06}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_a",
+  "dataset_id": "n12",
+  "started_at": "2026-05-19T15:59:03.544347+00:00",
+  "ended_at": "2026-05-19T15:59:21.207918+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_n12_b570ed79a8fcba38",
+    "problem_id": "v2p_n12_c64adeef051a1f27",
+    "dataset_id": "n12",
+    "template_id": "tpl_m4_window_partition_avg",
+    "template_name": "Window Partition Average",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "direction_consistency",
+    "intended_facet_id": "conditional_rate_shift",
+    "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 direction_consistency with semantic role filtered_stable_view. Focus on group_col=feature_2, measure_col=feature_2.",
+    "bindings": {
+      "group_col": "feature_2",
+      "measure_col": "feature_2",
+      "top_k": 18,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 104.84,
+      "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_rate_shift",
+      "template_selection_mode=rule",
+      "problem_index_within_template=2",
+      "sql_variant_index=2/2",
+      "binding_index=133"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 12,
+    "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",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/sql/v2q_n12_b570ed79a8fcba38.sql",
+  "usage_summary": {
+    "dataset_id": "n12",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_n12_b570ed79a8fcba38",
+    "api_calls": 0,
+    "input_tokens": 13467,
+    "cached_input_tokens": 12672,
+    "output_tokens": 632,
+    "total_tokens": 14099,
+    "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": 16273.27,
+    "sql_execution_elapsed_ms_total": 381.06,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:59:06.773980+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": 3225.41, "started_at": "2026-05-19T15:59:03.547844+00:00", "ended_at": "2026-05-19T15:59:06.773279+00:00", "prompt_metrics": {"chars": 4635, "bytes_utf8": 4635, "lines": 144, "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\":\"019e40f6-4ca2-71c2-bd8c-062e1971db4c\"}\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": "2026-05-19T15:59:20.823848+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": 13047.86, "started_at": "2026-05-19T15:59:07.775206+00:00", "ended_at": "2026-05-19T15:59:20.823110+00:00", "prompt_metrics": {"chars": 4635, "bytes_utf8": 4635, "lines": 144, "estimated_tokens": null}, "response_metrics": {"chars": 445, "bytes_utf8": 445, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13467, "cached_input_tokens": 12672, "output_tokens": 632, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"feature_2\\\",\\n       AVG(CAST(\\\"feature_2\\\" AS REAL)) OVER (PARTITION BY \\\"feature_2\\\") AS avg_measure\\nFROM \\\"n12\\\"\\nWHERE \\\"feature_2\\\" IS NOT NULL\\nORDER BY avg_measure DESC;\",\"notes\":\"Uses the Window Partition Average template with group_col and measure_col both bound to \\\"feature_2\\\". CAST is added because the schema stores numeric-looking values as TEXT in SQLite.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "n12",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_n12_b570ed79a8fcba38",
+  "api_calls": 0,
+  "input_tokens": 13467,
+  "cached_input_tokens": 12672,
+  "output_tokens": 632,
+  "total_tokens": 14099,
+  "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": 16273.27,
+  "sql_execution_elapsed_ms_total": 381.06,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b570ed79a8fcba38/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b9c691a810178daa/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=feature_3, measure_col=feature_3.
+Result preview: [{"feature_3": "255", "total_measure": 1196205.0}, {"feature_3": "162", "total_measure": 620622.0}, {"feature_3": "131", "total_measure": 496752.0}, {"feature_3": "132", "total_measure": 495924.0}, {"feature_3": "129", "total_measure": 453822.0}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_a/n12/artifacts/v2q_n12_b9c691a810178daa/generated_sql.sql

@@ -0,0 +1,19 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_a
+-- sql_source_dataset_id: n12
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_conditional_contrast
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_n12_b9c691a810178daa
+-- problem_id: v2p_n12_bfb971d2fe798f10
+-- realization_mode: agent
+-- source_kind: agent
+SELECT
+  "feature_3",
+  SUM(CAST("feature_3" AS REAL)) AS "total_measure"
+FROM "n12"
+GROUP BY "feature_3"
+ORDER BY "total_measure" DESC;