Add files using upload-large-folder tool

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_033e8d40b1584219/final_answer.txt

@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"date_added": "January 1, 2020", "support": 110, "avg_response": 2004.2727272727273}, {"date_added": "November 1, 2019", "support": 91, "avg_response": 2000.6923076923076}, {"date_added": "March 1, 2018", "support": 75, "avg_response": 2010.24}, {"date_added": "December 31, 2019", "support": 74, "avg_response": 1998.7567567567567}, {"date_added": "October 1, 2018", "support": 71, "avg_response": 2013.5070422535211}]}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_033e8d40b1584219/generated_sql.sql

@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_c17_033e8d40b1584219
+-- problem_id: v2p_c17_ebc150ac48ffbe4e
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "date_added",
+    COUNT(*) AS support,
+    AVG("release_year") AS avg_response
+FROM "c17"
+GROUP BY "date_added"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_033e8d40b1584219/query_results.jsonl

@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_b\n-- sql_source_dataset_id: c17\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_c17_033e8d40b1584219\n-- problem_id: v2p_c17_ebc150ac48ffbe4e\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"date_added\",\n    COUNT(*) AS support,\n    AVG(\"release_year\") AS avg_response\nFROM \"c17\"\nGROUP BY \"date_added\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_b\\n-- sql_source_dataset_id: c17\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_c17_033e8d40b1584219\\n-- problem_id: v2p_c17_ebc150ac48ffbe4e\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"date_added\\\",\\n    COUNT(*) AS support,\\n    AVG(\\\"release_year\\\") AS avg_response\\nFROM \\\"c17\\\"\\nGROUP BY \\\"date_added\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"date_added\", \"support\", \"avg_response\"], \"rows\": [{\"date_added\": \"January 1, 2020\", \"support\": 110, \"avg_response\": 2004.2727272727273}, {\"date_added\": \"November 1, 2019\", \"support\": 91, \"avg_response\": 2000.6923076923076}, {\"date_added\": \"March 1, 2018\", \"support\": 75, \"avg_response\": 2010.24}, {\"date_added\": \"December 31, 2019\", \"support\": 74, \"avg_response\": 1998.7567567567567}, {\"date_added\": \"October 1, 2018\", \"support\": 71, \"avg_response\": 2013.5070422535211}, {\"date_added\": \"October 1, 2019\", \"support\": 62, \"avg_response\": 2003.258064516129}, {\"date_added\": \"November 1, 2018\", \"support\": 60, \"avg_response\": 2012.5}, {\"date_added\": \"July 1, 2021\", \"support\": 60, \"avg_response\": 2007.1166666666666}, {\"date_added\": \"September 1, 2021\", \"support\": 56, \"avg_response\": 2003.9285714285713}, {\"date_added\": \"January 1, 2018\", \"support\": 55, \"avg_response\": 2011.4727272727273}, {\"date_added\": \"July 1, 2019\", \"support\": 52, \"avg_response\": 2011.3076923076924}, {\"date_added\": \"June 2, 2021\", \"support\": 51, \"avg_response\": 2008.8235294117646}, {\"date_added\": \"January 1, 2021\", \"support\": 49, \"avg_response\": 2005.4285714285713}, {\"date_added\": \"October 1, 2017\", \"support\": 47, \"avg_response\": 2013.9574468085107}, {\"date_added\": \"April 1, 2018\", \"support\": 44, \"avg_response\": 2007.4318181818182}, {\"date_added\": \"April 1, 2020\", \"support\": 43, \"avg_response\": 2008.8139534883721}, {\"date_added\": \"May 1, 2018\", \"support\": 42, \"avg_response\": 2016.3333333333333}, {\"date_added\": \"July 1, 2017\", \"support\": 42, \"avg_response\": 2006.857142857143}, {\"date_added\": \"February 1, 2019\", \"support\": 41, \"avg_response\": 2015.2439024390244}, {\"date_added\": \"August 1, 2017\", \"support\": 40, \"avg_response\": 2014.95}, {\"date_added\": \"July 1, 2018\", \"support\": 40, \"avg_response\": 2014.075}, {\"date_added\": \"July 6, 2021\", \"support\": 39, \"avg_response\": 2015.6666666666667}, {\"date_added\": \"September 1, 2017\", \"support\": 38, \"avg_response\": 2007.1052631578948}, {\"date_added\": \"August 1, 2021\", \"support\": 38, \"avg_response\": 2006.0526315789473}, {\"date_added\": \"August 1, 2018\", \"support\": 37, \"avg_response\": 2012.081081081081}, {\"date_added\": \"January 1, 2019\", \"support\": 37, \"avg_response\": 2008.054054054054}, {\"date_added\": \"October 1, 2020\", \"support\": 33, \"avg_response\": 2014.060606060606}, {\"date_added\": \"November 1, 2017\", \"support\": 33, \"avg_response\": 2012.7575757575758}, {\"date_added\": \"June 1, 2017\", \"support\": 33, \"avg_response\": 2010.8484848484848}, {\"date_added\": \"November 1, 2020\", \"support\": 33, \"avg_response\": 2010.6969696969697}, {\"date_added\": \"May 1, 2021\", \"support\": 33, \"avg_response\": 2010.2424242424242}, {\"date_added\": \"January 1, 2016\", \"support\": 33, \"avg_response\": 2006.3333333333333}, {\"date_added\": \"April 1, 2021\", \"support\": 32, \"avg_response\": 2012.15625}, {\"date_added\": \"September 1, 2019\", \"support\": 31, \"avg_response\": 2010.4516129032259}, {\"date_added\": \"March 31, 2017\", \"support\": 31, \"avg_response\": 1984.516129032258}, {\"date_added\": \"March 1, 2019\", \"support\": 30, \"avg_response\": 2015.2333333333333}, {\"date_added\": \"November 20, 2019\", \"support\": 30, \"avg_response\": 2006.2}, {\"date_added\": \"December 1, 2018\", \"support\": 29, \"avg_response\": 2014.5862068965516}, {\"date_added\": \"July 5, 2020\", \"support\": 29, \"avg_response\": 2013.7586206896551}, {\"date_added\": \"December 15, 2019\", \"support\": 29, \"avg_response\": 2011.2068965517242}, {\"date_added\": \"April 1, 2019\", \"support\": 28, \"avg_response\": 2013.8214285714287}, {\"date_added\": \"December 1, 2020\", \"support\": 28, \"avg_response\": 2011.857142857143}, {\"date_added\": \"December 1, 2019\", \"support\": 27, \"avg_response\": 2014.2962962962963}, {\"date_added\": \"August 27, 2021\", \"support\": 27, \"avg_response\": 2011.962962962963}, {\"date_added\": \"April 1, 2017\", \"support\": 27, \"avg_response\": 2011.111111111111}, {\"date_added\": \"December 31, 2018\", \"support\": 27, \"avg_response\": 2006.888888888889}, {\"date_added\": \"September 1, 2020\", \"support\": 26, \"avg_response\": 2014.6923076923076}, {\"date_added\": \"December 1, 2017\", \"support\": 26, \"avg_response\": 2014.2692307692307}, {\"date_added\": \"August 1, 2019\", \"support\": 26, \"avg_response\": 2004.8076923076924}, {\"date_added\": \"December 15, 2017\", \"support\": 25, \"avg_response\": 2014.76}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 5.26}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_033e8d40b1584219/run_manifest.json

@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T16:03:15.514122+00:00",
+  "ended_at": "2026-05-19T16:03:15.520159+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_033e8d40b1584219",
+    "problem_id": "v2p_c17_ebc150ac48ffbe4e",
+    "dataset_id": "c17",
+    "template_id": "tpl_cardinality_high_card_response_stability",
+    "template_name": "High-Cardinality Response Stability",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "high_cardinality_response_stability",
+    "intended_facet_id": "target_cardinality_cross_section",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=release_year, key_col=date_added.",
+    "bindings": {
+      "key_col": "date_added",
+      "measure_col": "release_year",
+      "min_support": 5
+    },
+    "binding_roles": [
+      "key_col",
+      "target_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {key_col},\n    COUNT(*) AS support,\n    AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;",
+    "notes": [
+      "default_facets=target_cardinality_cross_section",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=6",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "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_b/c17/sql/v2q_c17_033e8d40b1584219.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_033e8d40b1584219/usage_summary.json

@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/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=release_year, measure_col=release_year.
+Result preview: [{"release_year": "2018", "total_measure": 2314646}, {"release_year": "2017", "total_measure": 2081544}, {"release_year": "2019", "total_measure": 2079570}, {"release_year": "2020", "total_measure": 1925060}, {"release_year": "2016", "total_measure": 1818432}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/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: c17
+-- 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_c17_14bb0fa770f6753e
+-- problem_id: v2p_c17_2ae92b92b3b08e06
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "release_year", SUM("release_year") AS total_measure
+FROM "c17"
+GROUP BY "release_year"
+ORDER BY total_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/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 \"release_year\", SUM(\"release_year\") AS total_measure\nFROM \"c17\"\nGROUP BY \"release_year\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"release_year\\\", SUM(\\\"release_year\\\") AS total_measure\\nFROM \\\"c17\\\"\\nGROUP BY \\\"release_year\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"release_year\", \"total_measure\"], \"rows\": [{\"release_year\": \"2018\", \"total_measure\": 2314646}, {\"release_year\": \"2017\", \"total_measure\": 2081544}, {\"release_year\": \"2019\", \"total_measure\": 2079570}, {\"release_year\": \"2020\", \"total_measure\": 1925060}, {\"release_year\": \"2016\", \"total_measure\": 1818432}, {\"release_year\": \"2021\", \"total_measure\": 1196432}, {\"release_year\": \"2015\", \"total_measure\": 1128400}, {\"release_year\": \"2014\", \"total_measure\": 708928}, {\"release_year\": \"2013\", \"total_measure\": 579744}, {\"release_year\": \"2012\", \"total_measure\": 476844}, {\"release_year\": \"2010\", \"total_measure\": 389940}, {\"release_year\": \"2011\", \"total_measure\": 372035}, {\"release_year\": \"2009\", \"total_measure\": 305368}, {\"release_year\": \"2008\", \"total_measure\": 273088}, {\"release_year\": \"2006\", \"total_measure\": 192576}, {\"release_year\": \"2007\", \"total_measure\": 176616}, {\"release_year\": \"2005\", \"total_measure\": 160400}, {\"release_year\": \"2004\", \"total_measure\": 128256}, {\"release_year\": \"2003\", \"total_measure\": 122183}, {\"release_year\": \"2002\", \"total_measure\": 102102}, {\"release_year\": \"2001\", \"total_measure\": 90045}, {\"release_year\": \"1999\", \"total_measure\": 77961}, {\"release_year\": \"1997\", \"total_measure\": 75886}, {\"release_year\": \"2000\", \"total_measure\": 74000}, {\"release_year\": \"1998\", \"total_measure\": 71928}, {\"release_year\": \"1993\", \"total_measure\": 55804}, {\"release_year\": \"1995\", \"total_measure\": 49875}, {\"release_year\": \"1996\", \"total_measure\": 47904}, {\"release_year\": \"1992\", \"total_measure\": 45816}, {\"release_year\": \"1994\", \"total_measure\": 43868}, {\"release_year\": \"1990\", \"total_measure\": 43780}, {\"release_year\": \"1988\", \"total_measure\": 35784}, {\"release_year\": \"1991\", \"total_measure\": 33847}, {\"release_year\": \"1982\", \"total_measure\": 33694}, {\"release_year\": \"1989\", \"total_measure\": 31824}, {\"release_year\": \"1986\", \"total_measure\": 25818}, {\"release_year\": \"1981\", \"total_measure\": 25753}, {\"release_year\": \"1984\", \"total_measure\": 23808}, {\"release_year\": \"1983\", \"total_measure\": 21813}, {\"release_year\": \"1980\", \"total_measure\": 21780}, {\"release_year\": \"1979\", \"total_measure\": 21769}, {\"release_year\": \"1985\", \"total_measure\": 19850}, {\"release_year\": \"1973\", \"total_measure\": 19730}, {\"release_year\": \"1976\", \"total_measure\": 17784}, {\"release_year\": \"1987\", \"total_measure\": 15896}, {\"release_year\": \"1978\", \"total_measure\": 13846}, {\"release_year\": \"1977\", \"total_measure\": 13839}, {\"release_year\": \"1975\", \"total_measure\": 13825}, {\"release_year\": \"1974\", \"total_measure\": 13818}, {\"release_year\": \"1972\", \"total_measure\": 9860}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.23}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:28:35.853488+00:00",
+  "ended_at": "2026-05-19T15:28:46.655311+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_14bb0fa770f6753e",
+    "problem_id": "v2p_c17_2ae92b92b3b08e06",
+    "dataset_id": "c17",
+    "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=release_year, measure_col=release_year.",
+    "bindings": {
+      "group_col": "release_year",
+      "measure_col": "release_year",
+      "top_k": 11,
+      "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": 2019.0,
+      "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=2",
+      "sql_variant_index=1/2",
+      "binding_index=1"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "problem_index_within_template": 2,
+    "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/c17/sql/v2q_c17_14bb0fa770f6753e.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_14bb0fa770f6753e",
+    "api_calls": 0,
+    "input_tokens": 14647,
+    "cached_input_tokens": 0,
+    "output_tokens": 282,
+    "total_tokens": 14929,
+    "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": 10788.61,
+    "sql_execution_elapsed_ms_total": 7.23,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:28:46.645823+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": 10788.61, "started_at": "2026-05-19T15:28:35.855677+00:00", "ended_at": "2026-05-19T15:28:46.644310+00:00", "prompt_metrics": {"chars": 9185, "bytes_utf8": 9187, "lines": 240, "estimated_tokens": null}, "response_metrics": {"chars": 409, "bytes_utf8": 409, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14647, "cached_input_tokens": 0, "output_tokens": 282, "reasoning_output_tokens": 179}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"release_year\\\", SUM(\\\"release_year\\\") AS total_measure\\nFROM \\\"c17\\\"\\nGROUP BY \\\"release_year\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the provided grouped numeric sum template with group_col=\\\"release_year\\\" and measure_col=\\\"release_year\\\" on the single table \\\"c17\\\". SQLite will coerce numeric-looking TEXT values in \\\"release_year\\\" during SUM.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_14bb0fa770f6753e",
+  "api_calls": 0,
+  "input_tokens": 14647,
+  "cached_input_tokens": 0,
+  "output_tokens": 282,
+  "total_tokens": 14929,
+  "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": 10788.61,
+  "sql_execution_elapsed_ms_total": 7.23,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_14bb0fa770f6753e/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_17dbb084bc432c6f/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\n  \"type\",\n  AVG(CASE WHEN NULLIF(TRIM(\"release_year\"), '') IS NOT NULL THEN CAST(\"release_year\" AS REAL) END) OVER (PARTITION BY \"type\") AS avg_measure\nFROM \"c17\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT\\n  \\\"type\\\",\\n  AVG(CASE WHEN NULLIF(TRIM(\\\"release_year\\\"), '') IS NOT NULL THEN CAST(\\\"release_year\\\" AS REAL) END) OVER (PARTITION BY \\\"type\\\") AS avg_measure\\nFROM \\\"c17\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"type\", \"avg_measure\"], \"rows\": [{\"type\": \"TV Show\", \"avg_measure\": 2016.605754857997}, {\"type\": \"Movie\", \"avg_measure\": 2013.1215136193116}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 29.53}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/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=type, measure_col=release_year.
+Result preview: [{"type": "Movie", "total_measure": 12342448}, {"type": "TV Show", "total_measure": 5396437}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/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: c17
+-- family_id: subgroup_structure
+-- canonical_subitem_id: internal_profile_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: collapsed_target_view
+-- template_id: tpl_h2o_group_sum
+-- query_record_id: v2q_c17_28d8ddb9f1d016b0
+-- problem_id: v2p_c17_6e5833c7fb5d3f3c
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "type", SUM(CAST("release_year" AS INTEGER)) AS total_measure
+FROM "c17"
+GROUP BY "type"
+ORDER BY total_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/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 \"type\", SUM(CAST(\"release_year\" AS INTEGER)) AS total_measure\nFROM \"c17\"\nGROUP BY \"type\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"type\\\", SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS total_measure\\nFROM \\\"c17\\\"\\nGROUP BY \\\"type\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"type\", \"total_measure\"], \"rows\": [{\"type\": \"Movie\", \"total_measure\": 12342448}, {\"type\": \"TV Show\", \"total_measure\": 5396437}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.31}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:28:18.113097+00:00",
+  "ended_at": "2026-05-19T15:28:26.404583+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_28d8ddb9f1d016b0",
+    "problem_id": "v2p_c17_6e5833c7fb5d3f3c",
+    "dataset_id": "c17",
+    "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_distribution_shift",
+    "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=type, measure_col=release_year.",
+    "bindings": {
+      "group_col": "type",
+      "measure_col": "release_year",
+      "top_k": 10,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 2019.0,
+      "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=1",
+      "sql_variant_index=1/2",
+      "binding_index=0"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "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",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/sql/v2q_c17_28d8ddb9f1d016b0.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_28d8ddb9f1d016b0",
+    "api_calls": 0,
+    "input_tokens": 14645,
+    "cached_input_tokens": 0,
+    "output_tokens": 267,
+    "total_tokens": 14912,
+    "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": 8280.47,
+    "sql_execution_elapsed_ms_total": 5.31,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:28:26.397346+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": 8280.47, "started_at": "2026-05-19T15:28:18.115984+00:00", "ended_at": "2026-05-19T15:28:26.396493+00:00", "prompt_metrics": {"chars": 9170, "bytes_utf8": 9172, "lines": 240, "estimated_tokens": null}, "response_metrics": {"chars": 408, "bytes_utf8": 408, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14645, "cached_input_tokens": 0, "output_tokens": 267, "reasoning_output_tokens": 161}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"type\\\", SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS total_measure\\nFROM \\\"c17\\\"\\nGROUP BY \\\"type\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned grouped-sum template with group_col=\\\"type\\\" and measure_col=\\\"release_year\\\". CAST was added because \\\"release_year\\\" is stored as TEXT in the schema, and SQLite SUM should operate on numeric values.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_28d8ddb9f1d016b0",
+  "api_calls": 0,
+  "input_tokens": 14645,
+  "cached_input_tokens": 0,
+  "output_tokens": 267,
+  "total_tokens": 14912,
+  "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": 8280.47,
+  "sql_execution_elapsed_ms_total": 5.31,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_28d8ddb9f1d016b0/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_469f1b34a4b946a6/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:34:29.910593+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": 14947.33, "started_at": "2026-05-19T15:34:14.961716+00:00", "ended_at": "2026-05-19T15:34:29.909087+00:00", "prompt_metrics": {"chars": 9581, "bytes_utf8": 9583, "lines": 242, "estimated_tokens": null}, "response_metrics": {"chars": 803, "bytes_utf8": 803, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14762, "cached_input_tokens": 12032, "output_tokens": 751, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n  \\\"rating\\\",\\n  \\\"duration\\\",\\n  SUM(CAST(\\\"release_year\\\" AS REAL)) AS total_measure,\\n  SUM(CAST(\\\"release_year\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"release_year\\\" AS REAL))) OVER (PARTITION BY \\\"rating\\\"), 0) AS share_within_group\\nFROM \\\"c17\\\"\\nWHERE TRIM(COALESCE(\\\"rating\\\", '')) <> ''\\n  AND TRIM(COALESCE(\\\"duration\\\", '')) <> ''\\n  AND TRIM(COALESCE(\\\"release_year\\\", '')) <> ''\\nGROUP BY \\\"rating\\\", \\\"duration\\\"\\nORDER BY share_within_group DESC\\nLIMIT 16;\",\"notes\":\"Used the planned Within-Group Share of Total template with group_col=\\\"rating\\\", item_col=\\\"duration\\\", and measure_col=\\\"release_year\\\". Cast \\\"release_year\\\" to REAL because the schema stores it as TEXT, and filtered blank values in the bound columns.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_47a3ea86ae25b3b8/final_answer.txt

@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"release_year": "2018", "total_rows": 1147, "missing_rows": 0, "missing_rate": 0.0}, {"release_year": "2017", "total_rows": 1032, "missing_rows": 0, "missing_rate": 0.0}, {"release_year": "2019", "total_rows": 1030, "missing_rows": 0, "missing_rate": 0.0}, {"release_year": "2020", "total_rows": 953, "missing_rows": 0, "missing_rate": 0.0}, {"release_year": "2016", "total_rows": 902, "missing_rows": 0, "missing_rate": 0.0}]}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_47a3ea86ae25b3b8/generated_sql.sql

@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: missingness_structure
+-- canonical_subitem_id: co_missingness_pattern_consistency
+-- intended_facet_id: missing_rate_by_subgroup
+-- variant_semantic_role: missing_rate_by_subgroup
+-- template_id: tpl_missing_rate_by_subgroup
+-- query_record_id: v2q_c17_47a3ea86ae25b3b8
+-- problem_id: v2p_c17_b140464563a0b719
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "release_year",
+    COUNT(*) AS total_rows,
+    SUM(CASE WHEN "director" IS NULL THEN 1 ELSE 0 END) AS missing_rows,
+    AVG(CASE WHEN "director" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate
+FROM "c17"
+GROUP BY "release_year"
+ORDER BY missing_rate DESC, total_rows DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_47a3ea86ae25b3b8/query_results.jsonl

@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_b\n-- sql_source_dataset_id: c17\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_c17_47a3ea86ae25b3b8\n-- problem_id: v2p_c17_b140464563a0b719\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"release_year\",\n    COUNT(*) AS total_rows,\n    SUM(CASE WHEN \"director\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n    AVG(CASE WHEN \"director\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"c17\"\nGROUP BY \"release_year\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_b\\n-- sql_source_dataset_id: c17\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_c17_47a3ea86ae25b3b8\\n-- problem_id: v2p_c17_b140464563a0b719\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"release_year\\\",\\n    COUNT(*) AS total_rows,\\n    SUM(CASE WHEN \\\"director\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n    AVG(CASE WHEN \\\"director\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"c17\\\"\\nGROUP BY \\\"release_year\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"release_year\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"release_year\": \"2018\", \"total_rows\": 1147, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2017\", \"total_rows\": 1032, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2019\", \"total_rows\": 1030, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2020\", \"total_rows\": 953, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2016\", \"total_rows\": 902, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2021\", \"total_rows\": 592, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2015\", \"total_rows\": 560, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2014\", \"total_rows\": 352, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2013\", \"total_rows\": 288, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2012\", \"total_rows\": 237, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2010\", \"total_rows\": 194, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2011\", \"total_rows\": 185, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2009\", \"total_rows\": 152, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2008\", \"total_rows\": 136, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2006\", \"total_rows\": 96, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2007\", \"total_rows\": 88, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2005\", \"total_rows\": 80, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2004\", \"total_rows\": 64, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2003\", \"total_rows\": 61, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2002\", \"total_rows\": 51, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2001\", \"total_rows\": 45, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1999\", \"total_rows\": 39, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1997\", \"total_rows\": 38, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"2000\", \"total_rows\": 37, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1998\", \"total_rows\": 36, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1993\", \"total_rows\": 28, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1995\", \"total_rows\": 25, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1996\", \"total_rows\": 24, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1992\", \"total_rows\": 23, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1990\", \"total_rows\": 22, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1994\", \"total_rows\": 22, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1988\", \"total_rows\": 18, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1982\", \"total_rows\": 17, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1991\", \"total_rows\": 17, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1989\", \"total_rows\": 16, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1981\", \"total_rows\": 13, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1986\", \"total_rows\": 13, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1984\", \"total_rows\": 12, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1979\", \"total_rows\": 11, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1980\", \"total_rows\": 11, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1983\", \"total_rows\": 11, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1973\", \"total_rows\": 10, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1985\", \"total_rows\": 10, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1976\", \"total_rows\": 9, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1987\", \"total_rows\": 8, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1974\", \"total_rows\": 7, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1975\", \"total_rows\": 7, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1977\", \"total_rows\": 7, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1978\", \"total_rows\": 7, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"release_year\": \"1967\", \"total_rows\": 5, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 5.23}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_47a3ea86ae25b3b8/run_manifest.json

@@ -0,0 +1,59 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T16:03:15.323147+00:00",
+  "ended_at": "2026-05-19T16:03:15.329186+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_47a3ea86ae25b3b8",
+    "problem_id": "v2p_c17_b140464563a0b719",
+    "dataset_id": "c17",
+    "template_id": "tpl_missing_rate_by_subgroup",
+    "template_name": "Missing Rate by Subgroup",
+    "family_id": "missingness_structure",
+    "canonical_subitem_id": "co_missingness_pattern_consistency",
+    "intended_facet_id": "missing_rate_by_subgroup",
+    "variant_semantic_role": "missing_rate_by_subgroup",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": false,
+    "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=release_year, missing_col=director.",
+    "bindings": {
+      "missing_col": "director",
+      "group_col": "release_year"
+    },
+    "binding_roles": [
+      "missing_col",
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS total_rows,\n    SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n    AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;",
+    "notes": [
+      "default_facets=missing_rate_by_subgroup,missing_target_interaction",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "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_b/c17/sql/v2q_c17_47a3ea86ae25b3b8.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_47a3ea86ae25b3b8/usage_summary.json

@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_69ea826f95ed77a0/final_answer.txt

@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": []}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_69ea826f95ed77a0/run_manifest.json

@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T16:03:15.475351+00:00",
+  "ended_at": "2026-05-19T16:03:15.481048+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_69ea826f95ed77a0",
+    "problem_id": "v2p_c17_da345897263d1301",
+    "dataset_id": "c17",
+    "template_id": "tpl_cardinality_high_card_response_stability",
+    "template_name": "High-Cardinality Response Stability",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "high_cardinality_response_stability",
+    "intended_facet_id": "target_cardinality_cross_section",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=release_year, key_col=show_id.",
+    "bindings": {
+      "key_col": "show_id",
+      "measure_col": "release_year",
+      "min_support": 5
+    },
+    "binding_roles": [
+      "key_col",
+      "target_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {key_col},\n    COUNT(*) AS support,\n    AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;",
+    "notes": [
+      "default_facets=target_cardinality_cross_section",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 1,
+    "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/c17/sql/v2q_c17_69ea826f95ed77a0.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_6f33f54e77902efd/final_answer.txt

@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": []}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_6f33f54e77902efd/generated_sql.sql

@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- family_id: cardinality_structure
+-- canonical_subitem_id: high_cardinality_response_stability
+-- intended_facet_id: target_cardinality_cross_section
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_cardinality_high_card_response_stability
+-- query_record_id: v2q_c17_6f33f54e77902efd
+-- problem_id: v2p_c17_c8be8e0c23a88ec2
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "title",
+    COUNT(*) AS support,
+    AVG("release_year") AS avg_response
+FROM "c17"
+GROUP BY "title"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_6f33f54e77902efd/query_results.jsonl

@@ -0,0 +1 @@
+{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_b\n-- sql_source_dataset_id: c17\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_c17_6f33f54e77902efd\n-- problem_id: v2p_c17_c8be8e0c23a88ec2\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"title\",\n    COUNT(*) AS support,\n    AVG(\"release_year\") AS avg_response\nFROM \"c17\"\nGROUP BY \"title\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_b\\n-- sql_source_dataset_id: c17\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_c17_6f33f54e77902efd\\n-- problem_id: v2p_c17_c8be8e0c23a88ec2\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"title\\\",\\n    COUNT(*) AS support,\\n    AVG(\\\"release_year\\\") AS avg_response\\nFROM \\\"c17\\\"\\nGROUP BY \\\"title\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"title\", \"support\", \"avg_response\"], \"rows\": [], \"row_count_returned\": 0, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.64}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_6f33f54e77902efd/run_manifest.json

@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T16:03:15.481493+00:00",
+  "ended_at": "2026-05-19T16:03:15.488766+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_6f33f54e77902efd",
+    "problem_id": "v2p_c17_c8be8e0c23a88ec2",
+    "dataset_id": "c17",
+    "template_id": "tpl_cardinality_high_card_response_stability",
+    "template_name": "High-Cardinality Response Stability",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "high_cardinality_response_stability",
+    "intended_facet_id": "target_cardinality_cross_section",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=release_year, key_col=title.",
+    "bindings": {
+      "key_col": "title",
+      "measure_col": "release_year",
+      "min_support": 5
+    },
+    "binding_roles": [
+      "key_col",
+      "target_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "SELECT\n    {key_col},\n    COUNT(*) AS support,\n    AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;",
+    "notes": [
+      "default_facets=target_cardinality_cross_section",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=2",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "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_b/c17/sql/v2q_c17_6f33f54e77902efd.sql",
+  "usage_summary": {
+    "engine": "template",
+    "input_tokens": 0,
+    "cached_input_tokens": 0,
+    "output_tokens": 0,
+    "total_tokens": 0,
+    "estimated_total_tokens": 0,
+    "usage_source": "none"
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_6f33f54e77902efd/usage_summary.json

@@ -0,0 +1,9 @@
+{
+  "engine": "template",
+  "input_tokens": 0,
+  "cached_input_tokens": 0,
+  "output_tokens": 0,
+  "total_tokens": 0,
+  "estimated_total_tokens": 0,
+  "usage_source": "none"
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_814c15841852d542/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_814c15841852d542",
+  "api_calls": 0,
+  "input_tokens": 14766,
+  "cached_input_tokens": 13696,
+  "output_tokens": 738,
+  "total_tokens": 15504,
+  "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": 20997.4,
+  "sql_execution_elapsed_ms_total": 11.7,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_814c15841852d542/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/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=release_year.
+Result preview: [{"release_year": "2021"}, {"release_year": "2021"}, {"release_year": "2021"}, {"release_year": "2021"}, {"release_year": "2021"}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/generated_sql.sql

@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- 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_c17_83518fc4c2a17489
+-- problem_id: v2p_c17_27cef86f26a41175
+-- realization_mode: agent
+-- source_kind: agent
+WITH buckets AS (
+    SELECT
+        "release_year",
+        NTILE(10) OVER (ORDER BY CAST("release_year" AS INTEGER) DESC) AS tail_bucket
+    FROM "c17"
+    WHERE "release_year" IS NOT NULL
+      AND "release_year" <> ''
+)
+SELECT "release_year"
+FROM buckets
+WHERE tail_bucket = 1
+ORDER BY CAST("release_year" AS INTEGER) DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/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        \"release_year\",\n        NTILE(10) OVER (ORDER BY CAST(\"release_year\" AS INTEGER) DESC) AS tail_bucket\n    FROM \"c17\"\n    WHERE \"release_year\" IS NOT NULL\n      AND \"release_year\" <> ''\n)\nSELECT \"release_year\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"release_year\" AS INTEGER) DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT\\n        \\\"release_year\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"release_year\\\" AS INTEGER) DESC) AS tail_bucket\\n    FROM \\\"c17\\\"\\n    WHERE \\\"release_year\\\" IS NOT NULL\\n      AND \\\"release_year\\\" <> ''\\n)\\nSELECT \\\"release_year\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"release_year\\\" AS INTEGER) DESC;\", \"columns\": [\"release_year\"], \"rows\": [{\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}, {\"release_year\": \"2021\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 12.49}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/run_manifest.json

@@ -0,0 +1,87 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:42:39.700185+00:00",
+  "ended_at": "2026-05-19T15:42:53.934106+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_83518fc4c2a17489",
+    "problem_id": "v2p_c17_27cef86f26a41175",
+    "dataset_id": "c17",
+    "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=release_year.",
+    "bindings": {
+      "measure_col": "release_year",
+      "top_k": 11,
+      "top_n": 5,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 2019.0,
+      "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=7",
+      "sql_variant_index=1/1",
+      "binding_index=66"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 6,
+    "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/c17/sql/v2q_c17_83518fc4c2a17489.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_83518fc4c2a17489",
+    "api_calls": 0,
+    "input_tokens": 14700,
+    "cached_input_tokens": 13696,
+    "output_tokens": 439,
+    "total_tokens": 15139,
+    "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": 14216.99,
+    "sql_execution_elapsed_ms_total": 12.49,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:42:53.920202+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": 14216.99, "started_at": "2026-05-19T15:42:39.702401+00:00", "ended_at": "2026-05-19T15:42:53.919419+00:00", "prompt_metrics": {"chars": 9349, "bytes_utf8": 9351, "lines": 238, "estimated_tokens": null}, "response_metrics": {"chars": 668, "bytes_utf8": 668, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14700, "cached_input_tokens": 13696, "output_tokens": 439, "reasoning_output_tokens": 268}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n    SELECT\\n        \\\"release_year\\\",\\n        NTILE(10) OVER (ORDER BY CAST(\\\"release_year\\\" AS INTEGER) DESC) AS tail_bucket\\n    FROM \\\"c17\\\"\\n    WHERE \\\"release_year\\\" IS NOT NULL\\n      AND \\\"release_year\\\" <> ''\\n)\\nSELECT \\\"release_year\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"release_year\\\" AS INTEGER) DESC;\",\"notes\":\"Used the Quantile Tail Slice template with \\\"release_year\\\" as the measure column. Cast \\\"release_year\\\" to INTEGER for correct numeric ordering because the SQLite schema stores it as TEXT, and filtered out null/empty values before applying NTILE(10).\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_83518fc4c2a17489",
+  "api_calls": 0,
+  "input_tokens": 14700,
+  "cached_input_tokens": 13696,
+  "output_tokens": 439,
+  "total_tokens": 15139,
+  "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": 14216.99,
+  "sql_execution_elapsed_ms_total": 12.49,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_83518fc4c2a17489/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/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=type, measure_col=release_year.
+Result preview: [{"type": "Movie", "group_value": 12342448}, {"type": "TV Show", "group_value": 5396437}]

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/generated_sql.sql

@@ -0,0 +1,35 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- 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_c17_8e94c906ee91a3e0
+-- problem_id: v2p_c17_7fd833306ec4fdf8
+-- realization_mode: agent
+-- source_kind: agent
+WITH "grouped" AS (
+  SELECT
+    "type",
+    SUM(CAST("release_year" AS INTEGER)) AS "group_value"
+  FROM "c17"
+  WHERE "type" IS NOT NULL
+    AND TRIM("type") <> ''
+    AND "release_year" IS NOT NULL
+    AND TRIM("release_year") <> ''
+  GROUP BY "type"
+),
+"total" AS (
+  SELECT SUM("group_value") AS "total_value"
+  FROM "grouped"
+)
+SELECT
+  "g"."type",
+  "g"."group_value"
+FROM "grouped" AS "g"
+CROSS JOIN "total" AS "t"
+WHERE "g"."group_value" > "t"."total_value" * 0.05
+ORDER BY "g"."group_value" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/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\n    \"type\",\n    SUM(CAST(\"release_year\" AS INTEGER)) AS \"group_value\"\n  FROM \"c17\"\n  WHERE \"type\" IS NOT NULL\n    AND TRIM(\"type\") <> ''\n    AND \"release_year\" IS NOT NULL\n    AND TRIM(\"release_year\") <> ''\n  GROUP BY \"type\"\n),\n\"total\" AS (\n  SELECT SUM(\"group_value\") AS \"total_value\"\n  FROM \"grouped\"\n)\nSELECT\n  \"g\".\"type\",\n  \"g\".\"group_value\"\nFROM \"grouped\" AS \"g\"\nCROSS JOIN \"total\" AS \"t\"\nWHERE \"g\".\"group_value\" > \"t\".\"total_value\" * 0.05\nORDER BY \"g\".\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n  SELECT\\n    \\\"type\\\",\\n    SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS \\\"group_value\\\"\\n  FROM \\\"c17\\\"\\n  WHERE \\\"type\\\" IS NOT NULL\\n    AND TRIM(\\\"type\\\") <> ''\\n    AND \\\"release_year\\\" IS NOT NULL\\n    AND TRIM(\\\"release_year\\\") <> ''\\n  GROUP BY \\\"type\\\"\\n),\\n\\\"total\\\" AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM \\\"grouped\\\"\\n)\\nSELECT\\n  \\\"g\\\".\\\"type\\\",\\n  \\\"g\\\".\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS \\\"g\\\"\\nCROSS JOIN \\\"total\\\" AS \\\"t\\\"\\nWHERE \\\"g\\\".\\\"group_value\\\" > \\\"t\\\".\\\"total_value\\\" * 0.05\\nORDER BY \\\"g\\\".\\\"group_value\\\" DESC;\", \"columns\": [\"type\", \"group_value\"], \"rows\": [{\"type\": \"Movie\", \"group_value\": 12342448}, {\"type\": \"TV Show\", \"group_value\": 5396437}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 14.11}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:43:06.769015+00:00",
+  "ended_at": "2026-05-19T15:43:32.248107+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_8e94c906ee91a3e0",
+    "problem_id": "v2p_c17_7fd833306ec4fdf8",
+    "dataset_id": "c17",
+    "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=type, measure_col=release_year.",
+    "bindings": {
+      "group_col": "type",
+      "measure_col": "release_year",
+      "top_k": 17,
+      "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": 2018.0,
+      "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=1",
+      "sql_variant_index=2/2",
+      "binding_index=72"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 1,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/sql/v2q_c17_8e94c906ee91a3e0.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_8e94c906ee91a3e0",
+    "api_calls": 0,
+    "input_tokens": 14783,
+    "cached_input_tokens": 12032,
+    "output_tokens": 1167,
+    "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": 25456.24,
+    "sql_execution_elapsed_ms_total": 14.11,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:43:32.230633+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": 25456.24, "started_at": "2026-05-19T15:43:06.772775+00:00", "ended_at": "2026-05-19T15:43:32.229057+00:00", "prompt_metrics": {"chars": 9727, "bytes_utf8": 9729, "lines": 240, "estimated_tokens": null}, "response_metrics": {"chars": 900, "bytes_utf8": 900, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14783, "cached_input_tokens": 12032, "output_tokens": 1167, "reasoning_output_tokens": 900}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n  SELECT\\n    \\\"type\\\",\\n    SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS \\\"group_value\\\"\\n  FROM \\\"c17\\\"\\n  WHERE \\\"type\\\" IS NOT NULL\\n    AND TRIM(\\\"type\\\") <> ''\\n    AND \\\"release_year\\\" IS NOT NULL\\n    AND TRIM(\\\"release_year\\\") <> ''\\n  GROUP BY \\\"type\\\"\\n),\\n\\\"total\\\" AS (\\n  SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n  FROM \\\"grouped\\\"\\n)\\nSELECT\\n  \\\"g\\\".\\\"type\\\",\\n  \\\"g\\\".\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS \\\"g\\\"\\nCROSS JOIN \\\"total\\\" AS \\\"t\\\"\\nWHERE \\\"g\\\".\\\"group_value\\\" > \\\"t\\\".\\\"total_value\\\" * 0.05\\nORDER BY \\\"g\\\".\\\"group_value\\\" DESC;\",\"notes\":\"Applied the Relative-to-Total Extreme Threshold template with group_col=type and measure_col=release_year. Cast \\\"release_year\\\" to INTEGER because it is stored as TEXT in the schema, and filtered null/blank values for a stable aggregation view.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_8e94c906ee91a3e0",
+  "api_calls": 0,
+  "input_tokens": 14783,
+  "cached_input_tokens": 12032,
+  "output_tokens": 1167,
+  "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": 25456.24,
+  "sql_execution_elapsed_ms_total": 14.11,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_8e94c906ee91a3e0/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/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=rating, measure_col=release_year.
+Result preview: [{"rating": "66 min", "title": "Louis C.K.: Live at the Comedy Store", "total_measure": 2015, "share_within_group": 100.0}, {"rating": "74 min", "title": "Louis C.K. 2017", "total_measure": 2017, "share_within_group": 100.0}, {"rating": "84 min", "title": "Louis C.K.: Hilarious", "total_measure": 2010, "share_within_group": 100.0}, {"rating": "UR", "title": "Sex Doll", "total_measure": 2016, "share_within_group": 33.61120373457819}, {"rating": "UR", "title": "You Don't Mess with the Zohan", "total_measure": 2008, "share_within_group": 33.47782594198066}] Results were truncated.

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/generated_sql.sql

@@ -0,0 +1,22 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_b
+-- sql_source_dataset_id: c17
+-- 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_c17_fe1cd5791698df5e
+-- problem_id: v2p_c17_95b828b1ae90c402
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "rating", "title",
+       SUM(CAST("release_year" AS INTEGER)) AS total_measure,
+       SUM(CAST("release_year" AS INTEGER)) * 100.0 / SUM(SUM(CAST("release_year" AS INTEGER))) OVER (PARTITION BY "rating") AS share_within_group
+FROM "c17"
+WHERE "rating" IS NOT NULL AND "rating" <> ''
+  AND "title" IS NOT NULL AND "title" <> ''
+  AND "release_year" IS NOT NULL AND "release_year" <> ''
+GROUP BY "rating", "title"
+ORDER BY share_within_group DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/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 \"rating\", \"title\",\n       SUM(CAST(\"release_year\" AS INTEGER)) AS total_measure,\n       SUM(CAST(\"release_year\" AS INTEGER)) * 100.0 / SUM(SUM(CAST(\"release_year\" AS INTEGER))) OVER (PARTITION BY \"rating\") AS share_within_group\nFROM \"c17\"\nWHERE \"rating\" IS NOT NULL AND \"rating\" <> ''\n  AND \"title\" IS NOT NULL AND \"title\" <> ''\n  AND \"release_year\" IS NOT NULL AND \"release_year\" <> ''\nGROUP BY \"rating\", \"title\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"rating\\\", \\\"title\\\",\\n       SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS total_measure,\\n       SUM(CAST(\\\"release_year\\\" AS INTEGER)) * 100.0 / SUM(SUM(CAST(\\\"release_year\\\" AS INTEGER))) OVER (PARTITION BY \\\"rating\\\") AS share_within_group\\nFROM \\\"c17\\\"\\nWHERE \\\"rating\\\" IS NOT NULL AND \\\"rating\\\" <> ''\\n  AND \\\"title\\\" IS NOT NULL AND \\\"title\\\" <> ''\\n  AND \\\"release_year\\\" IS NOT NULL AND \\\"release_year\\\" <> ''\\nGROUP BY \\\"rating\\\", \\\"title\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"rating\", \"title\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"rating\": \"66 min\", \"title\": \"Louis C.K.: Live at the Comedy Store\", \"total_measure\": 2015, \"share_within_group\": 100.0}, {\"rating\": \"74 min\", \"title\": \"Louis C.K. 2017\", \"total_measure\": 2017, \"share_within_group\": 100.0}, {\"rating\": \"84 min\", \"title\": \"Louis C.K.: Hilarious\", \"total_measure\": 2010, \"share_within_group\": 100.0}, {\"rating\": \"UR\", \"title\": \"Sex Doll\", \"total_measure\": 2016, \"share_within_group\": 33.61120373457819}, {\"rating\": \"UR\", \"title\": \"You Don't Mess with the Zohan\", \"total_measure\": 2008, \"share_within_group\": 33.47782594198066}, {\"rating\": \"NC-17\", \"title\": \"Lady-Like\", \"total_measure\": 2018, \"share_within_group\": 33.38296112489661}, {\"rating\": \"NC-17\", \"title\": \"Swearnet: The Movie\", \"total_measure\": 2014, \"share_within_group\": 33.31679073614558}, {\"rating\": \"NC-17\", \"title\": \"Blue Is the Warmest Color\", \"total_measure\": 2013, \"share_within_group\": 33.30024813895782}, {\"rating\": \"UR\", \"title\": \"Immoral Tales\", \"total_measure\": 1974, \"share_within_group\": 32.91097032344115}, {\"rating\": \"TV-Y7-FV\", \"title\": \"Little Singham aur Kaal ka Mahajaal\", \"total_measure\": 2018, \"share_within_group\": 16.69286127884854}, {\"rating\": \"TV-Y7-FV\", \"title\": \"LEGO Ninjago: Masters of Spinjitzu: Day of the Departed\", \"total_measure\": 2016, \"share_within_group\": 16.67631731325999}, {\"rating\": \"TV-Y7-FV\", \"title\": \"Motu Patlu: King of Kings\", \"total_measure\": 2016, \"share_within_group\": 16.67631731325999}, {\"rating\": \"TV-Y7-FV\", \"title\": \"Oh No! It's an Alien Invasion\", \"total_measure\": 2014, \"share_within_group\": 16.659773347671436}, {\"rating\": \"TV-Y7-FV\", \"title\": \"Leo the Lion\", \"total_measure\": 2013, \"share_within_group\": 16.651501364877163}, {\"rating\": \"TV-Y7-FV\", \"title\": \"Dear Dracula\", \"total_measure\": 2012, \"share_within_group\": 16.643229382082886}, {\"rating\": \"G\", \"title\": \"Canvas\", \"total_measure\": 2020, \"share_within_group\": 2.4661213527041874}, {\"rating\": \"G\", \"title\": \"A Shaun the Sheep Movie: Farmageddon\", \"total_measure\": 2019, \"share_within_group\": 2.4649005005493834}, {\"rating\": \"G\", \"title\": \"A Champion Heart\", \"total_measure\": 2018, \"share_within_group\": 2.4636796483945793}, {\"rating\": \"G\", \"title\": \"Pup Star: World Tour\", \"total_measure\": 2018, \"share_within_group\": 2.4636796483945793}, {\"rating\": \"G\", \"title\": \"Ghost of the Mountains\", \"total_measure\": 2017, \"share_within_group\": 2.4624587962397753}, {\"rating\": \"G\", \"title\": \"Growing Up Wild\", \"total_measure\": 2016, \"share_within_group\": 2.461237944084971}, {\"rating\": \"G\", \"title\": \"Pup Star\", \"total_measure\": 2016, \"share_within_group\": 2.461237944084971}, {\"rating\": \"G\", \"title\": \"Tini: The New Life of Violetta\", \"total_measure\": 2016, \"share_within_group\": 2.461237944084971}, {\"rating\": \"G\", \"title\": \"The Pirate Fairy\", \"total_measure\": 2014, \"share_within_group\": 2.458796239775363}, {\"rating\": \"G\", \"title\": \"Tinker Bell and the Legend of the NeverBeast\", \"total_measure\": 2014, \"share_within_group\": 2.458796239775363}, {\"rating\": \"G\", \"title\": \"Justin Bieber: Never Say Never\", \"total_measure\": 2011, \"share_within_group\": 2.455133683310951}, {\"rating\": \"G\", \"title\": \"Garfield's Pet Force\", \"total_measure\": 2009, \"share_within_group\": 2.452691979001343}, {\"rating\": \"G\", \"title\": \"Hachi: A Dog's Tale\", \"total_measure\": 2009, \"share_within_group\": 2.452691979001343}, {\"rating\": \"G\", \"title\": \"Océans\", \"total_measure\": 2009, \"share_within_group\": 2.452691979001343}, {\"rating\": \"G\", \"title\": \"The Princess and the Frog\", \"total_measure\": 2009, \"share_within_group\": 2.452691979001343}, {\"rating\": \"G\", \"title\": \"The Pixar Story\", \"total_measure\": 2007, \"share_within_group\": 2.4502502746917347}, {\"rating\": \"G\", \"title\": \"Chicken Little\", \"total_measure\": 2005, \"share_within_group\": 2.4478085703821266}, {\"rating\": \"G\", \"title\": \"Tarzan 2\", \"total_measure\": 2005, \"share_within_group\": 2.4478085703821266}, {\"rating\": \"G\", \"title\": \"Balto 3: Wings of Change\", \"total_measure\": 2004, \"share_within_group\": 2.4465877182273226}, {\"rating\": \"G\", \"title\": \"Spookley the Square Pumpkin\", \"total_measure\": 2004, \"share_within_group\": 2.4465877182273226}, {\"rating\": \"G\", \"title\": \"The Polar Express\", \"total_measure\": 2004, \"share_within_group\": 2.4465877182273226}, {\"rating\": \"G\", \"title\": \"Balto 2: Wolf Quest\", \"total_measure\": 2001, \"share_within_group\": 2.4429251617629104}, {\"rating\": \"G\", \"title\": \"Jimmy Neutron: Boy Genius\", \"total_measure\": 2001, \"share_within_group\": 2.4429251617629104}, {\"rating\": \"G\", \"title\": \"An American Tail: The Treasures of Manhattan Island\", \"total_measure\": 2000, \"share_within_group\": 2.4417043096081064}, {\"rating\": \"G\", \"title\": \"Rugrats in Paris: The Movie\", \"total_measure\": 2000, \"share_within_group\": 2.4417043096081064}, {\"rating\": \"G\", \"title\": \"An American Tail: The Mystery of the Night Monster\", \"total_measure\": 1999, \"share_within_group\": 2.4404834574533023}, {\"rating\": \"G\", \"title\": \"Tarzan\", \"total_measure\": 1999, \"share_within_group\": 2.4404834574533023}, {\"rating\": \"G\", \"title\": \"The Rugrats Movie\", \"total_measure\": 1998, \"share_within_group\": 2.4392626052984983}, {\"rating\": \"G\", \"title\": \"Balto\", \"total_measure\": 1995, \"share_within_group\": 2.435600048834086}, {\"rating\": \"G\", \"title\": \"An American Tail: Fievel Goes West\", \"total_measure\": 1991, \"share_within_group\": 2.43071664021487}, {\"rating\": \"G\", \"title\": \"All Dogs Go to Heaven\", \"total_measure\": 1989, \"share_within_group\": 2.4282749359052618}, {\"rating\": \"G\", \"title\": \"An American Tail\", \"total_measure\": 1986, \"share_within_group\": 2.4246123794408496}, {\"rating\": \"G\", \"title\": \"For the Love of Benji\", \"total_measure\": 1977, \"share_within_group\": 2.413624710047613}, {\"rating\": \"G\", \"title\": \"Charlotte's Web\", \"total_measure\": 1973, \"share_within_group\": 2.408741301428397}, {\"rating\": \"G\", \"title\": \"Fiddler on the Roof\", \"total_measure\": 1971, \"share_within_group\": 2.406299597118789}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 62.88}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/run_manifest.json

@@ -0,0 +1,91 @@
+{
+  "run_id": "v2_cli_20260502_081223_b",
+  "dataset_id": "c17",
+  "started_at": "2026-05-19T15:36:19.980955+00:00",
+  "ended_at": "2026-05-19T15:36:35.097682+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c17_fe1cd5791698df5e",
+    "problem_id": "v2p_c17_95b828b1ae90c402",
+    "dataset_id": "c17",
+    "template_id": "tpl_tpcds_within_group_share",
+    "template_name": "Within-Group Share of Total",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "within_group_proportion",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=rating, measure_col=release_year.",
+    "bindings": {
+      "group_col": "rating",
+      "measure_col": "release_year",
+      "item_col": "title",
+      "top_k": 10,
+      "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": 2019.0,
+      "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",
+      "item_col",
+      "measure_col"
+    ],
+    "coverage_target_min": "5",
+    "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;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=7",
+      "sql_variant_index=1/2",
+      "binding_index=30"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 3,
+    "problem_index_within_template": 7,
+    "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/c17/sql/v2q_c17_fe1cd5791698df5e.sql",
+  "usage_summary": {
+    "dataset_id": "c17",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c17_fe1cd5791698df5e",
+    "api_calls": 0,
+    "input_tokens": 14763,
+    "cached_input_tokens": 12032,
+    "output_tokens": 726,
+    "total_tokens": 15489,
+    "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": 15046.02,
+    "sql_execution_elapsed_ms_total": 62.88,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:36:35.032378+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": 15046.02, "started_at": "2026-05-19T15:36:19.984618+00:00", "ended_at": "2026-05-19T15:36:35.030679+00:00", "prompt_metrics": {"chars": 9581, "bytes_utf8": 9583, "lines": 242, "estimated_tokens": null}, "response_metrics": {"chars": 765, "bytes_utf8": 765, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14763, "cached_input_tokens": 12032, "output_tokens": 726, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"rating\\\", \\\"title\\\",\\n       SUM(CAST(\\\"release_year\\\" AS INTEGER)) AS total_measure,\\n       SUM(CAST(\\\"release_year\\\" AS INTEGER)) * 100.0 / SUM(SUM(CAST(\\\"release_year\\\" AS INTEGER))) OVER (PARTITION BY \\\"rating\\\") AS share_within_group\\nFROM \\\"c17\\\"\\nWHERE \\\"rating\\\" IS NOT NULL AND \\\"rating\\\" <> ''\\n  AND \\\"title\\\" IS NOT NULL AND \\\"title\\\" <> ''\\n  AND \\\"release_year\\\" IS NOT NULL AND \\\"release_year\\\" <> ''\\nGROUP BY \\\"rating\\\", \\\"title\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"rating\\\", item_col=\\\"title\\\", and measure_col=\\\"release_year\\\". Cast \\\"release_year\\\" to INTEGER because it is stored as TEXT in the schema.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c17",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c17_fe1cd5791698df5e",
+  "api_calls": 0,
+  "input_tokens": 14763,
+  "cached_input_tokens": 12032,
+  "output_tokens": 726,
+  "total_tokens": 15489,
+  "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": 15046.02,
+  "sql_execution_elapsed_ms_total": 62.88,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_b/c17/artifacts/v2q_c17_fe1cd5791698df5e/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}