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Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_06329c2abcc4ed53/final_answer.txt

@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"nom_9": "163cc60fa", "support": 72, "avg_response": 1.5694444444444444}, {"nom_9": "21578b358", "support": 70, "avg_response": 1.4285714285714286}, {"nom_9": "e8be2364b", "support": 67, "avg_response": 1.5522388059701493}, {"nom_9": "412859a59", "support": 67, "avg_response": 1.328358208955224}, {"nom_9": "f12f038cc", "support": 66, "avg_response": 1.4696969696969697}]}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_06329c2abcc4ed53/generated_sql.sql

@@ -0,0 +1,21 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- 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_c14_06329c2abcc4ed53
+-- problem_id: v2p_c14_3a30ece7ea77ae47
+-- realization_mode: deterministic
+-- source_kind: deterministic
+SELECT
+    "nom_9",
+    COUNT(*) AS support,
+    AVG("ord_0") AS avg_response
+FROM "c14"
+GROUP BY "nom_9"
+HAVING COUNT(*) >= 5.0
+ORDER BY support DESC, avg_response DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_06329c2abcc4ed53/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_d\n-- sql_source_dataset_id: c14\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_c14_06329c2abcc4ed53\n-- problem_id: v2p_c14_3a30ece7ea77ae47\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n    \"nom_9\",\n    COUNT(*) AS support,\n    AVG(\"ord_0\") AS avg_response\nFROM \"c14\"\nGROUP BY \"nom_9\"\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_d\\n-- sql_source_dataset_id: c14\\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_c14_06329c2abcc4ed53\\n-- problem_id: v2p_c14_3a30ece7ea77ae47\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n    \\\"nom_9\\\",\\n    COUNT(*) AS support,\\n    AVG(\\\"ord_0\\\") AS avg_response\\nFROM \\\"c14\\\"\\nGROUP BY \\\"nom_9\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"nom_9\", \"support\", \"avg_response\"], \"rows\": [{\"nom_9\": \"163cc60fa\", \"support\": 72, \"avg_response\": 1.5694444444444444}, {\"nom_9\": \"21578b358\", \"support\": 70, \"avg_response\": 1.4285714285714286}, {\"nom_9\": \"e8be2364b\", \"support\": 67, \"avg_response\": 1.5522388059701493}, {\"nom_9\": \"412859a59\", \"support\": 67, \"avg_response\": 1.328358208955224}, {\"nom_9\": \"f12f038cc\", \"support\": 66, \"avg_response\": 1.4696969696969697}, {\"nom_9\": \"ca7ddfae9\", \"support\": 65, \"avg_response\": 1.5384615384615385}, {\"nom_9\": \"38039d3a8\", \"support\": 64, \"avg_response\": 1.65625}, {\"nom_9\": \"2257000b0\", \"support\": 64, \"avg_response\": 1.4375}, {\"nom_9\": \"f43b6639b\", \"support\": 63, \"avg_response\": 1.7142857142857142}, {\"nom_9\": \"971c72d33\", \"support\": 63, \"avg_response\": 1.5873015873015872}, {\"nom_9\": \"2668255cf\", \"support\": 63, \"avg_response\": 1.507936507936508}, {\"nom_9\": \"7d43106ff\", \"support\": 63, \"avg_response\": 1.4444444444444444}, {\"nom_9\": \"3a5b9bbd7\", \"support\": 63, \"avg_response\": 1.4126984126984128}, {\"nom_9\": \"3e1d307ac\", \"support\": 63, \"avg_response\": 1.380952380952381}, {\"nom_9\": \"a92c41029\", \"support\": 62, \"avg_response\": 1.6451612903225807}, {\"nom_9\": \"b043b3d84\", \"support\": 62, \"avg_response\": 1.6290322580645162}, {\"nom_9\": \"ae709c39d\", \"support\": 62, \"avg_response\": 1.5806451612903225}, {\"nom_9\": \"b37f33d00\", \"support\": 62, \"avg_response\": 1.532258064516129}, {\"nom_9\": \"8defee9b8\", \"support\": 62, \"avg_response\": 1.5}, {\"nom_9\": \"0a29d2401\", \"support\": 62, \"avg_response\": 1.467741935483871}, {\"nom_9\": \"d4d9cd1e9\", \"support\": 62, \"avg_response\": 1.4193548387096775}, {\"nom_9\": \"0e2bfc354\", \"support\": 62, \"avg_response\": 1.3709677419354838}, {\"nom_9\": \"912eb6e42\", \"support\": 62, \"avg_response\": 1.3709677419354838}, {\"nom_9\": \"8e6834928\", \"support\": 61, \"avg_response\": 1.6885245901639345}, {\"nom_9\": \"428d5bad6\", \"support\": 61, \"avg_response\": 1.5081967213114753}, {\"nom_9\": \"af920cd89\", \"support\": 61, \"avg_response\": 1.4754098360655739}, {\"nom_9\": \"9fbd214f0\", \"support\": 61, \"avg_response\": 1.459016393442623}, {\"nom_9\": \"a1d23b123\", \"support\": 61, \"avg_response\": 1.459016393442623}, {\"nom_9\": \"c1324082f\", \"support\": 61, \"avg_response\": 1.459016393442623}, {\"nom_9\": \"4ef13e388\", \"support\": 61, \"avg_response\": 1.4426229508196722}, {\"nom_9\": \"95db371aa\", \"support\": 61, \"avg_response\": 1.4426229508196722}, {\"nom_9\": \"d608ebad3\", \"support\": 61, \"avg_response\": 1.4426229508196722}, {\"nom_9\": \"1903e8cdf\", \"support\": 61, \"avg_response\": 1.4262295081967213}, {\"nom_9\": \"2b7212b50\", \"support\": 61, \"avg_response\": 1.4262295081967213}, {\"nom_9\": \"60f27e6b6\", \"support\": 61, \"avg_response\": 1.4098360655737705}, {\"nom_9\": \"fe5220394\", \"support\": 61, \"avg_response\": 1.4098360655737705}, {\"nom_9\": \"27c271936\", \"support\": 60, \"avg_response\": 1.6166666666666667}, {\"nom_9\": \"c54a4d273\", \"support\": 60, \"avg_response\": 1.6}, {\"nom_9\": \"9332ff270\", \"support\": 60, \"avg_response\": 1.55}, {\"nom_9\": \"b22e596ed\", \"support\": 60, \"avg_response\": 1.55}, {\"nom_9\": \"18e372a4d\", \"support\": 60, \"avg_response\": 1.5333333333333334}, {\"nom_9\": \"2533756c6\", \"support\": 60, \"avg_response\": 1.5}, {\"nom_9\": \"8dfb56d84\", \"support\": 60, \"avg_response\": 1.5}, {\"nom_9\": \"cefa8140e\", \"support\": 60, \"avg_response\": 1.4833333333333334}, {\"nom_9\": \"8e0450be1\", \"support\": 60, \"avg_response\": 1.4666666666666666}, {\"nom_9\": \"04ee2825d\", \"support\": 60, \"avg_response\": 1.4}, {\"nom_9\": \"fe7aa1794\", \"support\": 60, \"avg_response\": 1.4}, {\"nom_9\": \"770664efa\", \"support\": 60, \"avg_response\": 1.3}, {\"nom_9\": \"03dae55ac\", \"support\": 60, \"avg_response\": 1.2666666666666666}, {\"nom_9\": \"a16b1d8cd\", \"support\": 60, \"avg_response\": 1.2666666666666666}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 245.03}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_06329c2abcc4ed53/run_manifest.json

@@ -0,0 +1,60 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T16:12:58.795640+00:00",
+  "ended_at": "2026-05-19T16:12:59.043086+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_06329c2abcc4ed53",
+    "problem_id": "v2p_c14_3a30ece7ea77ae47",
+    "dataset_id": "c14",
+    "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=ord_0, key_col=nom_9.",
+    "bindings": {
+      "key_col": "nom_9",
+      "measure_col": "ord_0",
+      "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=9",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 9,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/sql/v2q_c14_06329c2abcc4ed53.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_d/c14/artifacts/v2q_c14_06329c2abcc4ed53/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_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/run_manifest.json

@@ -0,0 +1,72 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T16:06:17.104656+00:00",
+  "ended_at": "2026-05-19T16:06:24.481030+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_07a800fb6dea0c53",
+    "problem_id": "v2p_c14_342db65b37b53bad",
+    "dataset_id": "c14",
+    "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=ord_1, condition_col=ord_1.",
+    "bindings": {
+      "group_col": "ord_1",
+      "condition_col": "ord_1",
+      "condition_value": "Grandmaster",
+      "positive_value": "Grandmaster",
+      "negative_value": "Contributor",
+      "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": 2.5,
+      "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=6",
+      "sql_variant_index=1/2",
+      "binding_index=101"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "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",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_07a800fb6dea0c53/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:06:20.106643+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": 2981.44, "started_at": "2026-05-19T16:06:17.124402+00:00", "ended_at": "2026-05-19T16:06:20.105880+00:00", "prompt_metrics": {"chars": 11948, "bytes_utf8": 11948, "lines": 399, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-ea20-7500-960d-e8d8c0657793\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:06:24.480905+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3371.82, "started_at": "2026-05-19T16:06:21.108332+00:00", "ended_at": "2026-05-19T16:06:24.480195+00:00", "prompt_metrics": {"chars": 11948, "bytes_utf8": 11948, "lines": 399, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-f9b7-7053-8a49-879c9ee82008\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_09baa2b16984f8b1/final_answer.txt

@@ -0,0 +1 @@
+{"row_count": null, "preview_rows": [{"value_label": "2", "support": 45305, "support_share": 0.15101666666666666, "support_rank": 1}, {"value_label": "3", "support": 40867, "support_share": 0.13622333333333334, "support_rank": 2}, {"value_label": "1", "support": 40848, "support_share": 0.13616, "support_rank": 3}, {"value_label": "11", "support": 25732, "support_share": 0.08577333333333333, "support_rank": 4}, {"value_label": "12", "support": 25204, "support_share": 0.08401333333333333, "support_rank": 5}]}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_09baa2b16984f8b1/generated_sql.sql

@@ -0,0 +1,25 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- family_id: cardinality_structure
+-- canonical_subitem_id: support_rank_profile_consistency
+-- intended_facet_id: value_imbalance_profile
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_cardinality_support_rank_profile
+-- query_record_id: v2q_c14_09baa2b16984f8b1
+-- problem_id: v2p_c14_497a56ca1796c4f9
+-- realization_mode: deterministic
+-- source_kind: deterministic
+WITH grouped AS (
+    SELECT "month" AS value_label, COUNT(*) AS support
+    FROM "c14"
+    GROUP BY "month"
+)
+SELECT
+    value_label,
+    support,
+    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,
+    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank
+FROM grouped
+ORDER BY support DESC, value_label;

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_09baa2b16984f8b1/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_d\n-- sql_source_dataset_id: c14\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_c14_09baa2b16984f8b1\n-- problem_id: v2p_c14_497a56ca1796c4f9\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n    SELECT \"month\" AS value_label, COUNT(*) AS support\n    FROM \"c14\"\n    GROUP BY \"month\"\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: c14\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_c14_09baa2b16984f8b1\\n-- problem_id: v2p_c14_497a56ca1796c4f9\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n    SELECT \\\"month\\\" AS value_label, COUNT(*) AS support\\n    FROM \\\"c14\\\"\\n    GROUP BY \\\"month\\\"\\n)\\nSELECT\\n    value_label,\\n    support,\\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"2\", \"support\": 45305, \"support_share\": 0.15101666666666666, \"support_rank\": 1}, {\"value_label\": \"3\", \"support\": 40867, \"support_share\": 0.13622333333333334, \"support_rank\": 2}, {\"value_label\": \"1\", \"support\": 40848, \"support_share\": 0.13616, \"support_rank\": 3}, {\"value_label\": \"11\", \"support\": 25732, \"support_share\": 0.08577333333333333, \"support_rank\": 4}, {\"value_label\": \"12\", \"support\": 25204, \"support_share\": 0.08401333333333333, \"support_rank\": 5}, {\"value_label\": \"4\", \"support\": 24920, \"support_share\": 0.08306666666666666, \"support_rank\": 6}, {\"value_label\": \"9\", \"support\": 24857, \"support_share\": 0.08285666666666666, \"support_rank\": 7}, {\"value_label\": \"10\", \"support\": 22112, \"support_share\": 0.07370666666666667, \"support_rank\": 8}, {\"value_label\": \"7\", \"support\": 19867, \"support_share\": 0.06622333333333333, \"support_rank\": 9}, {\"value_label\": \"8\", \"support\": 18730, \"support_share\": 0.062433333333333334, \"support_rank\": 10}, {\"value_label\": \"5\", \"support\": 10995, \"support_share\": 0.03665, \"support_rank\": 11}, {\"value_label\": \"6\", \"support\": 563, \"support_share\": 0.0018766666666666667, \"support_rank\": 12}], \"row_count_returned\": 12, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 164.64}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_09baa2b16984f8b1/run_manifest.json

@@ -0,0 +1,57 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T16:12:56.883876+00:00",
+  "ended_at": "2026-05-19T16:12:57.050181+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_09baa2b16984f8b1",
+    "problem_id": "v2p_c14_497a56ca1796c4f9",
+    "dataset_id": "c14",
+    "template_id": "tpl_cardinality_support_rank_profile",
+    "template_name": "Cardinality Support Rank Profile",
+    "family_id": "cardinality_structure",
+    "canonical_subitem_id": "support_rank_profile_consistency",
+    "intended_facet_id": "value_imbalance_profile",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "template_fixed",
+    "source_kind": "deterministic",
+    "realization_mode": "deterministic",
+    "gate_priority": "deterministic",
+    "extended_family": true,
+    "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=month.",
+    "bindings": {
+      "group_col": "month"
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "enumerate_all_applicable",
+    "runtime_sql_skeleton": "WITH grouped AS (\n    SELECT {group_col} AS value_label, COUNT(*) AS support\n    FROM {table}\n    GROUP BY {group_col}\n)\nSELECT\n    value_label,\n    support,\n    CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n    ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;",
+    "notes": [
+      "default_facets=support_concentration,value_imbalance_profile",
+      "template_selection_mode=deterministic",
+      "problem_index_within_template=12",
+      "sql_variant_index=1/1"
+    ],
+    "template_selection_mode": "deterministic",
+    "selected_template_rank": 0,
+    "problem_index_within_template": 12,
+    "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_d/c14/sql/v2q_c14_09baa2b16984f8b1.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_d/c14/artifacts/v2q_c14_09baa2b16984f8b1/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_d/c14/artifacts/v2q_c14_0ce9623600e98e90/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=bin_1, measure_col=ord_0.
+Result preview: [{"bin_1": "0", "total_measure": 329987}, {"bin_1": "1", "total_measure": 113883}]

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0ce9623600e98e90/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- 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_c14_0ce9623600e98e90
+-- problem_id: v2p_c14_f07b4d5c228a6f1a
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "bin_1", SUM(CAST("ord_0" AS INTEGER)) AS total_measure
+FROM "c14"
+GROUP BY "bin_1"
+ORDER BY total_measure DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0ce9623600e98e90/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 \"bin_1\", SUM(CAST(\"ord_0\" AS INTEGER)) AS total_measure\nFROM \"c14\"\nGROUP BY \"bin_1\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"bin_1\\\", SUM(CAST(\\\"ord_0\\\" AS INTEGER)) AS total_measure\\nFROM \\\"c14\\\"\\nGROUP BY \\\"bin_1\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"bin_1\", \"total_measure\"], \"rows\": [{\"bin_1\": \"0\", \"total_measure\": 329987}, {\"bin_1\": \"1\", \"total_measure\": 113883}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 135.91}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0ce9623600e98e90/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T15:28:50.428302+00:00",
+  "ended_at": "2026-05-19T15:28:59.847915+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_0ce9623600e98e90",
+    "problem_id": "v2p_c14_f07b4d5c228a6f1a",
+    "dataset_id": "c14",
+    "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=bin_1, measure_col=ord_0.",
+    "bindings": {
+      "group_col": "bin_1",
+      "measure_col": "ord_0",
+      "top_k": 16,
+      "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": 2.32,
+      "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=2/2",
+      "binding_index=1"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 1,
+    "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_d/c14/sql/v2q_c14_0ce9623600e98e90.sql",
+  "usage_summary": {
+    "dataset_id": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_0ce9623600e98e90",
+    "api_calls": 0,
+    "input_tokens": 15910,
+    "cached_input_tokens": 12032,
+    "output_tokens": 388,
+    "total_tokens": 16298,
+    "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": 9264.87,
+    "sql_execution_elapsed_ms_total": 135.91,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0ce9623600e98e90/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0ce9623600e98e90/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:28:59.710066+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": 9264.87, "started_at": "2026-05-19T15:28:50.444206+00:00", "ended_at": "2026-05-19T15:28:59.709105+00:00", "prompt_metrics": {"chars": 11685, "bytes_utf8": 11685, "lines": 396, "estimated_tokens": null}, "response_metrics": {"chars": 340, "bytes_utf8": 340, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15910, "cached_input_tokens": 12032, "output_tokens": 388, "reasoning_output_tokens": 288}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"bin_1\\\", SUM(CAST(\\\"ord_0\\\" AS INTEGER)) AS total_measure\\nFROM \\\"c14\\\"\\nGROUP BY \\\"bin_1\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned grouped numeric sum template with \\\"bin_1\\\" as the grouping column and cast \\\"ord_0\\\" from TEXT to INTEGER so SQLite sums it numerically.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0ce9623600e98e90/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c14",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c14_0ce9623600e98e90",
+  "api_calls": 0,
+  "input_tokens": 15910,
+  "cached_input_tokens": 12032,
+  "output_tokens": 388,
+  "total_tokens": 16298,
+  "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": 9264.87,
+  "sql_execution_elapsed_ms_total": 135.91,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0ce9623600e98e90/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=ord_2, measure_col=id.
+Result preview: [{"ord_2": "Warm", "percentile_measure": 285429.74999999994}, {"ord_2": "Freezing", "percentile_measure": 285268.75}, {"ord_2": "Boiling Hot", "percentile_measure": 285078.69999999995}, {"ord_2": "Lava Hot", "percentile_measure": 284865.3}, {"ord_2": "Hot", "percentile_measure": 284379.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/generated_sql.sql

@@ -0,0 +1,65 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: focused_target_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_c14_0e7cbd59ed81486a
+-- problem_id: v2p_c14_237b1bb1096a39f6
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ordered" AS (
+  SELECT
+    "ord_2",
+    CAST("id" AS REAL) AS "measure",
+    ROW_NUMBER() OVER (
+      PARTITION BY "ord_2"
+      ORDER BY CAST("id" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "ord_2"
+    ) AS "n"
+  FROM "c14"
+  WHERE "id" IS NOT NULL
+),
+"params" AS (
+  SELECT DISTINCT
+    "ord_2",
+    (1.0 + 0.95 * ("n" - 1)) AS "pos",
+    CAST((1.0 + 0.95 * ("n" - 1)) AS INTEGER) AS "lo",
+    CASE
+      WHEN (1.0 + 0.95 * ("n" - 1)) = CAST((1.0 + 0.95 * ("n" - 1)) AS INTEGER)
+        THEN CAST((1.0 + 0.95 * ("n" - 1)) AS INTEGER)
+      ELSE CAST((1.0 + 0.95 * ("n" - 1)) AS INTEGER) + 1
+    END AS "hi"
+  FROM "ordered"
+),
+"picked" AS (
+  SELECT
+    "p"."ord_2",
+    "p"."pos",
+    "p"."lo",
+    "p"."hi",
+    MAX(CASE WHEN "o"."rn" = "p"."lo" THEN "o"."measure" END) AS "lo_measure",
+    MAX(CASE WHEN "o"."rn" = "p"."hi" THEN "o"."measure" END) AS "hi_measure"
+  FROM "params" AS "p"
+  JOIN "ordered" AS "o"
+    ON "o"."ord_2" IS "p"."ord_2"
+   AND "o"."rn" IN ("p"."lo", "p"."hi")
+  GROUP BY
+    "p"."ord_2",
+    "p"."pos",
+    "p"."lo",
+    "p"."hi"
+)
+SELECT
+  "ord_2",
+  CASE
+    WHEN "lo" = "hi" THEN "lo_measure"
+    ELSE "lo_measure" + ("pos" - "lo") * ("hi_measure" - "lo_measure")
+  END AS "percentile_measure"
+FROM "picked"
+ORDER BY "percentile_measure" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/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_grouped_percentile_point\nWITH \"ordered\" AS (\n  SELECT\n    \"ord_2\",\n    CAST(\"id\" AS REAL) AS \"measure\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"ord_2\"\n      ORDER BY CAST(\"id\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"ord_2\"\n    ) AS \"n\"\n  FROM \"c14\"\n  WHERE \"id\" IS NOT NULL\n),\n\"params\" AS (\n  SELECT DISTINCT\n    \"ord_2\",\n    (1.0 + 0.95 * (\"n\" - 1)) AS \"pos\",\n    CAST((1.0 + 0.95 * (\"n\" - 1)) AS INTEGER) AS \"lo\",\n    CASE\n      WHEN (1.0 + 0.95 * (\"n\" - 1)) = CAST((1.0 + 0.95 * (\"n\" - 1)) AS INTEGER)\n        THEN CAST((1.0 + 0.95 * (\"n\" - 1)) AS INTEGER)\n      ELSE CAST((1.0 + 0.95 * (\"n\" - 1)) AS INTEGER) + 1\n    END AS \"hi\"\n  FROM \"ordered\"\n),\n\"picked\" AS (\n  SELECT\n    \"p\".\"ord_2\",\n    \"p\".\"pos\",\n    \"p\".\"lo\",\n    \"p\".\"hi\",\n    MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"lo\" THEN \"o\".\"measure\" END) AS \"lo_measure\",\n    MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"hi\" THEN \"o\".\"measure\" END) AS \"hi_measure\"\n  FROM \"params\" AS \"p\"\n  JOIN \"ordered\" AS \"o\"\n    ON \"o\".\"ord_2\" IS \"p\".\"ord_2\"\n   AND \"o\".\"rn\" IN (\"p\".\"lo\", \"p\".\"hi\")\n  GROUP BY\n    \"p\".\"ord_2\",\n    \"p\".\"pos\",\n    \"p\".\"lo\",\n    \"p\".\"hi\"\n)\nSELECT\n  \"ord_2\",\n  CASE\n    WHEN \"lo\" = \"hi\" THEN \"lo_measure\"\n    ELSE \"lo_measure\" + (\"pos\" - \"lo\") * (\"hi_measure\" - \"lo_measure\")\n  END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"ord_2\\\",\\n    CAST(\\\"id\\\" AS REAL) AS \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n      ORDER BY CAST(\\\"id\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n    ) AS \\\"n\\\"\\n  FROM \\\"c14\\\"\\n  WHERE \\\"id\\\" IS NOT NULL\\n),\\n\\\"params\\\" AS (\\n  SELECT DISTINCT\\n    \\\"ord_2\\\",\\n    (1.0 + 0.95 * (\\\"n\\\" - 1)) AS \\\"pos\\\",\\n    CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"lo\\\",\\n    CASE\\n      WHEN (1.0 + 0.95 * (\\\"n\\\" - 1)) = CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER)\\n        THEN CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER)\\n      ELSE CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n    END AS \\\"hi\\\"\\n  FROM \\\"ordered\\\"\\n),\\n\\\"picked\\\" AS (\\n  SELECT\\n    \\\"p\\\".\\\"ord_2\\\",\\n    \\\"p\\\".\\\"pos\\\",\\n    \\\"p\\\".\\\"lo\\\",\\n    \\\"p\\\".\\\"hi\\\",\\n    MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"lo\\\" THEN \\\"o\\\".\\\"measure\\\" END) AS \\\"lo_measure\\\",\\n    MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"hi\\\" THEN \\\"o\\\".\\\"measure\\\" END) AS \\\"hi_measure\\\"\\n  FROM \\\"params\\\" AS \\\"p\\\"\\n  JOIN \\\"ordered\\\" AS \\\"o\\\"\\n    ON \\\"o\\\".\\\"ord_2\\\" IS \\\"p\\\".\\\"ord_2\\\"\\n   AND \\\"o\\\".\\\"rn\\\" IN (\\\"p\\\".\\\"lo\\\", \\\"p\\\".\\\"hi\\\")\\n  GROUP BY\\n    \\\"p\\\".\\\"ord_2\\\",\\n    \\\"p\\\".\\\"pos\\\",\\n    \\\"p\\\".\\\"lo\\\",\\n    \\\"p\\\".\\\"hi\\\"\\n)\\nSELECT\\n  \\\"ord_2\\\",\\n  CASE\\n    WHEN \\\"lo\\\" = \\\"hi\\\" THEN \\\"lo_measure\\\"\\n    ELSE \\\"lo_measure\\\" + (\\\"pos\\\" - \\\"lo\\\") * (\\\"hi_measure\\\" - \\\"lo_measure\\\")\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"ord_2\", \"percentile_measure\"], \"rows\": [{\"ord_2\": \"Warm\", \"percentile_measure\": 285429.74999999994}, {\"ord_2\": \"Freezing\", \"percentile_measure\": 285268.75}, {\"ord_2\": \"Boiling Hot\", \"percentile_measure\": 285078.69999999995}, {\"ord_2\": \"Lava Hot\", \"percentile_measure\": 284865.3}, {\"ord_2\": \"Hot\", \"percentile_measure\": 284379.0}, {\"ord_2\": \"Cold\", \"percentile_measure\": 284373.3}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 974.56}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T15:52:24.440214+00:00",
+  "ended_at": "2026-05-19T15:53:07.875727+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_0e7cbd59ed81486a",
+    "problem_id": "v2p_c14_237b1bb1096a39f6",
+    "dataset_id": "c14",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=ord_2, measure_col=id.",
+    "bindings": {
+      "group_col": "ord_2",
+      "measure_col": "id",
+      "top_k": 14,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 172611.0,
+      "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},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=1/2",
+      "binding_index=84"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "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_d/c14/sql/v2q_c14_0e7cbd59ed81486a.sql",
+  "usage_summary": {
+    "dataset_id": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_0e7cbd59ed81486a",
+    "api_calls": 0,
+    "input_tokens": 15944,
+    "cached_input_tokens": 14720,
+    "output_tokens": 3001,
+    "total_tokens": 18945,
+    "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": 42441.53,
+    "sql_execution_elapsed_ms_total": 974.56,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:53:06.899179+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": 42441.53, "started_at": "2026-05-19T15:52:24.456327+00:00", "ended_at": "2026-05-19T15:53:06.897888+00:00", "prompt_metrics": {"chars": 11860, "bytes_utf8": 11860, "lines": 396, "estimated_tokens": null}, "response_metrics": {"chars": 1828, "bytes_utf8": 1828, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15944, "cached_input_tokens": 14720, "output_tokens": 3001, "reasoning_output_tokens": 2340}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n  SELECT\\n    \\\"ord_2\\\",\\n    CAST(\\\"id\\\" AS REAL) AS \\\"measure\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n      ORDER BY CAST(\\\"id\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n    ) AS \\\"n\\\"\\n  FROM \\\"c14\\\"\\n  WHERE \\\"id\\\" IS NOT NULL\\n),\\n\\\"params\\\" AS (\\n  SELECT DISTINCT\\n    \\\"ord_2\\\",\\n    (1.0 + 0.95 * (\\\"n\\\" - 1)) AS \\\"pos\\\",\\n    CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"lo\\\",\\n    CASE\\n      WHEN (1.0 + 0.95 * (\\\"n\\\" - 1)) = CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER)\\n        THEN CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER)\\n      ELSE CAST((1.0 + 0.95 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n    END AS \\\"hi\\\"\\n  FROM \\\"ordered\\\"\\n),\\n\\\"picked\\\" AS (\\n  SELECT\\n    \\\"p\\\".\\\"ord_2\\\",\\n    \\\"p\\\".\\\"pos\\\",\\n    \\\"p\\\".\\\"lo\\\",\\n    \\\"p\\\".\\\"hi\\\",\\n    MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"lo\\\" THEN \\\"o\\\".\\\"measure\\\" END) AS \\\"lo_measure\\\",\\n    MAX(CASE WHEN"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c14",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c14_0e7cbd59ed81486a",
+  "api_calls": 0,
+  "input_tokens": 15944,
+  "cached_input_tokens": 14720,
+  "output_tokens": 3001,
+  "total_tokens": 18945,
+  "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": 42441.53,
+  "sql_execution_elapsed_ms_total": 974.56,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_0e7cbd59ed81486a/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/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 count_distribution. Focus on group_col=nom_4, measure_col=ord_0.
+Result preview: [{"nom_4": "Oboe", "group_value": 136622.0}, {"nom_4": "Piano", "group_value": 124817.0}, {"nom_4": "Bassoon", "group_value": 101561.0}, {"nom_4": "Theremin", "group_value": 80870.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/generated_sql.sql

@@ -0,0 +1,26 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_mass_similarity
+-- intended_facet_id: tail_ranked_signal
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_tpch_relative_total_threshold
+-- query_record_id: v2q_c14_13902a2eaa059ea8
+-- problem_id: v2p_c14_e03e78166dcefc27
+-- realization_mode: agent
+-- source_kind: agent
+WITH grouped AS (
+    SELECT "nom_4", SUM(CAST("ord_0" AS REAL)) AS group_value
+    FROM "c14"
+    GROUP BY "nom_4"
+), total AS (
+    SELECT SUM(group_value) AS total_value
+    FROM grouped
+)
+SELECT g."nom_4", 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_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/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 \"nom_4\", SUM(CAST(\"ord_0\" AS REAL)) AS group_value\n    FROM \"c14\"\n    GROUP BY \"nom_4\"\n), total AS (\n    SELECT SUM(group_value) AS total_value\n    FROM grouped\n)\nSELECT g.\"nom_4\", 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 \\\"nom_4\\\", SUM(CAST(\\\"ord_0\\\" AS REAL)) AS group_value\\n    FROM \\\"c14\\\"\\n    GROUP BY \\\"nom_4\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"nom_4\\\", 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\": [\"nom_4\", \"group_value\"], \"rows\": [{\"nom_4\": \"Oboe\", \"group_value\": 136622.0}, {\"nom_4\": \"Piano\", \"group_value\": 124817.0}, {\"nom_4\": \"Bassoon\", \"group_value\": 101561.0}, {\"nom_4\": \"Theremin\", \"group_value\": 80870.0}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 163.01}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T15:52:12.329878+00:00",
+  "ended_at": "2026-05-19T15:52:24.439660+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_13902a2eaa059ea8",
+    "problem_id": "v2p_c14_e03e78166dcefc27",
+    "dataset_id": "c14",
+    "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": "count_distribution",
+    "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 count_distribution. Focus on group_col=nom_4, measure_col=ord_0.",
+    "bindings": {
+      "group_col": "nom_4",
+      "measure_col": "ord_0",
+      "top_k": 16,
+      "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": 2.32,
+      "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=10",
+      "sql_variant_index=2/2",
+      "binding_index=81"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 7,
+    "problem_index_within_template": 10,
+    "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_d/c14/sql/v2q_c14_13902a2eaa059ea8.sql",
+  "usage_summary": {
+    "dataset_id": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_13902a2eaa059ea8",
+    "api_calls": 0,
+    "input_tokens": 16046,
+    "cached_input_tokens": 12032,
+    "output_tokens": 571,
+    "total_tokens": 16617,
+    "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": 11927.18,
+    "sql_execution_elapsed_ms_total": 163.01,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:52:24.274640+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": 11927.18, "started_at": "2026-05-19T15:52:12.346273+00:00", "ended_at": "2026-05-19T15:52:24.273481+00:00", "prompt_metrics": {"chars": 12239, "bytes_utf8": 12239, "lines": 396, "estimated_tokens": null}, "response_metrics": {"chars": 581, "bytes_utf8": 581, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16046, "cached_input_tokens": 12032, "output_tokens": 571, "reasoning_output_tokens": 400}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n    SELECT \\\"nom_4\\\", SUM(CAST(\\\"ord_0\\\" AS REAL)) AS group_value\\n    FROM \\\"c14\\\"\\n    GROUP BY \\\"nom_4\\\"\\n), total AS (\\n    SELECT SUM(group_value) AS total_value\\n    FROM grouped\\n)\\nSELECT g.\\\"nom_4\\\", 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\":\"Uses the required template with group_col=\\\"nom_4\\\" and measure_col=\\\"ord_0\\\". CAST is applied because \\\"ord_0\\\" is stored as TEXT in the SQLite schema.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c14",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c14_13902a2eaa059ea8",
+  "api_calls": 0,
+  "input_tokens": 16046,
+  "cached_input_tokens": 12032,
+  "output_tokens": 571,
+  "total_tokens": 16617,
+  "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": 11927.18,
+  "sql_execution_elapsed_ms_total": 163.01,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_13902a2eaa059ea8/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_139564d59acf46fe/run_manifest.json

@@ -0,0 +1,67 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T16:07:55.725816+00:00",
+  "ended_at": "2026-05-19T16:08:03.883175+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_139564d59acf46fe",
+    "problem_id": "v2p_c14_b72b766c0ac6cf2c",
+    "dataset_id": "c14",
+    "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=id.",
+    "bindings": {
+      "measure_col": "id",
+      "top_k": 12,
+      "top_n": 3,
+      "num_tiles": 10,
+      "percentile_value": 0.95,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.1,
+      "baseline_multiplier": 1.5,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 5,
+      "measure_threshold": 172611.0,
+      "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=5",
+      "sql_variant_index=1/1",
+      "binding_index=112"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 10,
+    "problem_index_within_template": 5,
+    "sql_variant_index": 1,
+    "sql_variant_total": 1
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_139564d59acf46fe/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:08:00.218686+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": 4476.85, "started_at": "2026-05-19T16:07:55.740975+00:00", "ended_at": "2026-05-19T16:08:00.217866+00:00", "prompt_metrics": {"chars": 11624, "bytes_utf8": 11624, "lines": 394, "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\":\"019e40fe-6b72-7b92-b25a-808d0c127953\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:08:03.883071+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2662.17, "started_at": "2026-05-19T16:08:01.220090+00:00", "ended_at": "2026-05-19T16:08:03.882289+00:00", "prompt_metrics": {"chars": 11624, "bytes_utf8": 11624, "lines": 394, "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\":\"019e40fe-80da-7652-b688-989dbdc67356\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=month, measure_col=id.
+Result preview: [{"month": "5", "percentile_measure": 270999.0}, {"month": "9", "percentile_measure": 270943.0}, {"month": "11", "percentile_measure": 270581.0}, {"month": "8", "percentile_measure": 270424.0}, {"month": "2", "percentile_measure": 270027.0}]

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/generated_sql.sql

@@ -0,0 +1,41 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_c14_14d281320e5b21e9
+-- problem_id: v2p_c14_5ab54d22f4d066d1
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "month",
+    CAST("id" AS REAL) AS "id_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "month"
+      ORDER BY CAST("id" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "month"
+    ) AS "cnt"
+  FROM "c14"
+  WHERE "month" IS NOT NULL
+    AND "id" IS NOT NULL
+),
+"percentile_points" AS (
+  SELECT
+    "month",
+    "id_value" AS "percentile_measure"
+  FROM "ranked"
+  WHERE "cnt" >= 5
+    AND "rn" = ((9 * "cnt") + 9) / 10
+)
+SELECT
+  "month",
+  "percentile_measure"
+FROM "percentile_points"
+ORDER BY "percentile_measure" DESC, "month";

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/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_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"month\",\n    CAST(\"id\" AS REAL) AS \"id_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"month\"\n      ORDER BY CAST(\"id\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"month\"\n    ) AS \"cnt\"\n  FROM \"c14\"\n  WHERE \"month\" IS NOT NULL\n    AND \"id\" IS NOT NULL\n),\n\"percentile_points\" AS (\n  SELECT\n    \"month\",\n    \"id_value\" AS \"percentile_measure\"\n  FROM \"ranked\"\n  WHERE \"cnt\" >= 5\n    AND \"rn\" = ((9 * \"cnt\") + 9) / 10\n)\nSELECT\n  \"month\",\n  \"percentile_measure\"\nFROM \"percentile_points\"\nORDER BY \"percentile_measure\" DESC, \"month\";", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"month\\\",\\n    CAST(\\\"id\\\" AS REAL) AS \\\"id_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"month\\\"\\n      ORDER BY CAST(\\\"id\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"month\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"c14\\\"\\n  WHERE \\\"month\\\" IS NOT NULL\\n    AND \\\"id\\\" IS NOT NULL\\n),\\n\\\"percentile_points\\\" AS (\\n  SELECT\\n    \\\"month\\\",\\n    \\\"id_value\\\" AS \\\"percentile_measure\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cnt\\\" >= 5\\n    AND \\\"rn\\\" = ((9 * \\\"cnt\\\") + 9) / 10\\n)\\nSELECT\\n  \\\"month\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentile_points\\\"\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"month\\\";\", \"columns\": [\"month\", \"percentile_measure\"], \"rows\": [{\"month\": \"5\", \"percentile_measure\": 270999.0}, {\"month\": \"9\", \"percentile_measure\": 270943.0}, {\"month\": \"11\", \"percentile_measure\": 270581.0}, {\"month\": \"8\", \"percentile_measure\": 270424.0}, {\"month\": \"2\", \"percentile_measure\": 270027.0}, {\"month\": \"12\", \"percentile_measure\": 270009.0}, {\"month\": \"3\", \"percentile_measure\": 269852.0}, {\"month\": \"7\", \"percentile_measure\": 269782.0}, {\"month\": \"1\", \"percentile_measure\": 269568.0}, {\"month\": \"4\", \"percentile_measure\": 269484.0}, {\"month\": \"10\", \"percentile_measure\": 269272.0}, {\"month\": \"6\", \"percentile_measure\": 261582.0}], \"row_count_returned\": 12, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 731.63}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T15:58:21.412479+00:00",
+  "ended_at": "2026-05-19T15:58:47.795518+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_14d281320e5b21e9",
+    "problem_id": "v2p_c14_5ab54d22f4d066d1",
+    "dataset_id": "c14",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=month, measure_col=id.",
+    "bindings": {
+      "group_col": "month",
+      "measure_col": "id",
+      "top_k": 18,
+      "top_n": 4,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 150351.84,
+      "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 {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=2/2",
+      "binding_index=88"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "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_d/c14/sql/v2q_c14_14d281320e5b21e9.sql",
+  "usage_summary": {
+    "dataset_id": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_14d281320e5b21e9",
+    "api_calls": 0,
+    "input_tokens": 15940,
+    "cached_input_tokens": 14720,
+    "output_tokens": 1259,
+    "total_tokens": 17199,
+    "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": 25632.96,
+    "sql_execution_elapsed_ms_total": 731.63,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/trace.jsonl

@@ -0,0 +1 @@
+{"timestamp": "2026-05-19T15:58:47.062302+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": 25632.96, "started_at": "2026-05-19T15:58:21.428525+00:00", "ended_at": "2026-05-19T15:58:47.061512+00:00", "prompt_metrics": {"chars": 11861, "bytes_utf8": 11861, "lines": 396, "estimated_tokens": null}, "response_metrics": {"chars": 922, "bytes_utf8": 922, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15940, "cached_input_tokens": 14720, "output_tokens": 1259, "reasoning_output_tokens": 977}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"month\\\",\\n    CAST(\\\"id\\\" AS REAL) AS \\\"id_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"month\\\"\\n      ORDER BY CAST(\\\"id\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"month\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"c14\\\"\\n  WHERE \\\"month\\\" IS NOT NULL\\n    AND \\\"id\\\" IS NOT NULL\\n),\\n\\\"percentile_points\\\" AS (\\n  SELECT\\n    \\\"month\\\",\\n    \\\"id_value\\\" AS \\\"percentile_measure\\\"\\n  FROM \\\"ranked\\\"\\n  WHERE \\\"cnt\\\" >= 5\\n    AND \\\"rn\\\" = ((9 * \\\"cnt\\\") + 9) / 10\\n)\\nSELECT\\n  \\\"month\\\",\\n  \\\"percentile_measure\\\"\\nFROM \\\"percentile_points\\\"\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"month\\\";\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses the nearest-rank 90th percentile per month via window functions. \\\"id\\\" is stored as TEXT in the schema, so it is cast to REAL before ordering.\"}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c14",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c14_14d281320e5b21e9",
+  "api_calls": 0,
+  "input_tokens": 15940,
+  "cached_input_tokens": 14720,
+  "output_tokens": 1259,
+  "total_tokens": 17199,
+  "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": 25632.96,
+  "sql_execution_elapsed_ms_total": 731.63,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_14d281320e5b21e9/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=ord_2, measure_col=id.
+Result preview: [{"ord_2": "Freezing", "percentile_measure": 270550.5}, {"ord_2": "Warm", "percentile_measure": 270172.50000000006}, {"ord_2": "Boiling Hot", "percentile_measure": 269901.8}, {"ord_2": "Hot", "percentile_measure": 269775.4}, {"ord_2": "Lava Hot", "percentile_measure": 269529.6}]

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/generated_sql.sql

@@ -0,0 +1,65 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- family_id: tail_rarity_structure
+-- canonical_subitem_id: tail_concentration_consistency
+-- intended_facet_id: rare_target_concentration
+-- variant_semantic_role: ranked_signal_view
+-- template_id: tpl_grouped_percentile_point
+-- query_record_id: v2q_c14_16198038f30f6c74
+-- problem_id: v2p_c14_0f817401af7c6850
+-- realization_mode: agent
+-- source_kind: agent
+WITH "ranked" AS (
+  SELECT
+    "ord_2",
+    CAST("id" AS REAL) AS "measure_value",
+    ROW_NUMBER() OVER (
+      PARTITION BY "ord_2"
+      ORDER BY CAST("id" AS REAL)
+    ) AS "rn",
+    COUNT(*) OVER (
+      PARTITION BY "ord_2"
+    ) AS "cnt"
+  FROM "c14"
+  WHERE "ord_2" IS NOT NULL
+    AND "id" IS NOT NULL
+),
+"positions" AS (
+  SELECT DISTINCT
+    "ord_2",
+    (1.0 + 0.9 * ("cnt" - 1)) AS "pos",
+    CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) AS "lower_rn",
+    CASE
+      WHEN (1.0 + 0.9 * ("cnt" - 1)) = CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER)
+        THEN CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER)
+      ELSE CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + 1
+    END AS "upper_rn"
+  FROM "ranked"
+),
+"picked" AS (
+  SELECT
+    p."ord_2",
+    p."pos",
+    p."lower_rn",
+    p."upper_rn",
+    MAX(CASE WHEN r."rn" = p."lower_rn" THEN r."measure_value" END) AS "lower_value",
+    MAX(CASE WHEN r."rn" = p."upper_rn" THEN r."measure_value" END) AS "upper_value"
+  FROM "positions" AS p
+  JOIN "ranked" AS r
+    ON r."ord_2" = p."ord_2"
+  GROUP BY
+    p."ord_2",
+    p."pos",
+    p."lower_rn",
+    p."upper_rn"
+)
+SELECT
+  "ord_2",
+  CASE
+    WHEN "lower_rn" = "upper_rn" THEN "lower_value"
+    ELSE "lower_value" + ("pos" - "lower_rn") * ("upper_value" - "lower_value")
+  END AS "percentile_measure"
+FROM "picked"
+ORDER BY "percentile_measure" DESC;

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/query_results.jsonl

@@ -0,0 +1 @@
+{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n  SELECT\n    \"ord_2\",\n    CAST(\"id\" AS REAL) AS \"measure_value\",\n    ROW_NUMBER() OVER (\n      PARTITION BY \"ord_2\"\n      ORDER BY CAST(\"id\" AS REAL)\n    ) AS \"rn\",\n    COUNT(*) OVER (\n      PARTITION BY \"ord_2\"\n    ) AS \"cnt\"\n  FROM \"c14\"\n  WHERE \"ord_2\" IS NOT NULL\n    AND \"id\" IS NOT NULL\n),\n\"positions\" AS (\n  SELECT DISTINCT\n    \"ord_2\",\n    (1.0 + 0.9 * (\"cnt\" - 1)) AS \"pos\",\n    CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER) AS \"lower_rn\",\n    CASE\n      WHEN (1.0 + 0.9 * (\"cnt\" - 1)) = CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER)\n        THEN CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER)\n      ELSE CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER) + 1\n    END AS \"upper_rn\"\n  FROM \"ranked\"\n),\n\"picked\" AS (\n  SELECT\n    p.\"ord_2\",\n    p.\"pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\",\n    MAX(CASE WHEN r.\"rn\" = p.\"lower_rn\" THEN r.\"measure_value\" END) AS \"lower_value\",\n    MAX(CASE WHEN r.\"rn\" = p.\"upper_rn\" THEN r.\"measure_value\" END) AS \"upper_value\"\n  FROM \"positions\" AS p\n  JOIN \"ranked\" AS r\n    ON r.\"ord_2\" = p.\"ord_2\"\n  GROUP BY\n    p.\"ord_2\",\n    p.\"pos\",\n    p.\"lower_rn\",\n    p.\"upper_rn\"\n)\nSELECT\n  \"ord_2\",\n  CASE\n    WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_value\"\n    ELSE \"lower_value\" + (\"pos\" - \"lower_rn\") * (\"upper_value\" - \"lower_value\")\n  END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"ord_2\\\",\\n    CAST(\\\"id\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n      ORDER BY CAST(\\\"id\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"c14\\\"\\n  WHERE \\\"ord_2\\\" IS NOT NULL\\n    AND \\\"id\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT DISTINCT\\n    \\\"ord_2\\\",\\n    (1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n    CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN (1.0 + 0.9 * (\\\"cnt\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n        THEN CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n      ELSE CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) + 1\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ranked\\\"\\n),\\n\\\"picked\\\" AS (\\n  SELECT\\n    p.\\\"ord_2\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\",\\n    MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"measure_value\\\" END) AS \\\"lower_value\\\",\\n    MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN r.\\\"measure_value\\\" END) AS \\\"upper_value\\\"\\n  FROM \\\"positions\\\" AS p\\n  JOIN \\\"ranked\\\" AS r\\n    ON r.\\\"ord_2\\\" = p.\\\"ord_2\\\"\\n  GROUP BY\\n    p.\\\"ord_2\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\"\\n)\\nSELECT\\n  \\\"ord_2\\\",\\n  CASE\\n    WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_value\\\"\\n    ELSE \\\"lower_value\\\" + (\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_value\\\" - \\\"lower_value\\\")\\n  END AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"ord_2\", \"percentile_measure\"], \"rows\": [{\"ord_2\": \"Freezing\", \"percentile_measure\": 270550.5}, {\"ord_2\": \"Warm\", \"percentile_measure\": 270172.50000000006}, {\"ord_2\": \"Boiling Hot\", \"percentile_measure\": 269901.8}, {\"ord_2\": \"Hot\", \"percentile_measure\": 269775.4}, {\"ord_2\": \"Lava Hot\", \"percentile_measure\": 269529.6}, {\"ord_2\": \"Cold\", \"percentile_measure\": 269342.1}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1221.23}"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/run_manifest.json

@@ -0,0 +1,89 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T15:53:07.876265+00:00",
+  "ended_at": "2026-05-19T15:53:34.392399+00:00",
+  "status": "completed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_16198038f30f6c74",
+    "problem_id": "v2p_c14_0f817401af7c6850",
+    "dataset_id": "c14",
+    "template_id": "tpl_grouped_percentile_point",
+    "template_name": "Grouped Percentile Point",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_concentration_consistency",
+    "intended_facet_id": "rare_target_concentration",
+    "variant_semantic_role": "ranked_signal_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=ord_2, measure_col=id.",
+    "bindings": {
+      "group_col": "ord_2",
+      "measure_col": "id",
+      "top_k": 19,
+      "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": 150351.84,
+      "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 {group_col},\n       PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;",
+    "notes": [
+      "default_facets=rare_target_concentration",
+      "template_selection_mode=rule",
+      "problem_index_within_template=1",
+      "sql_variant_index=2/2",
+      "binding_index=84"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 8,
+    "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_d/c14/sql/v2q_c14_16198038f30f6c74.sql",
+  "usage_summary": {
+    "dataset_id": "c14",
+    "model": "v2-cli:codex",
+    "run_id": "v2q_c14_16198038f30f6c74",
+    "api_calls": 0,
+    "input_tokens": 15944,
+    "cached_input_tokens": 12032,
+    "output_tokens": 1149,
+    "total_tokens": 17093,
+    "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": 24271.67,
+    "sql_execution_elapsed_ms_total": 1221.23,
+    "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/cli/conversation.jsonl",
+    "note": "Executed through a local AI CLI with structured usage metadata."
+  }
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T15:53:10.928608+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": 3035.61, "started_at": "2026-05-19T15:53:07.892067+00:00", "ended_at": "2026-05-19T15:53:10.927705+00:00", "prompt_metrics": {"chars": 11861, "bytes_utf8": 11861, "lines": 396, "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\":\"019e40f0-df5e-7a41-9df2-4dc44132174c\"}\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": "2026-05-19T15:53:33.169109+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": 21236.06, "started_at": "2026-05-19T15:53:11.930473+00:00", "ended_at": "2026-05-19T15:53:33.166583+00:00", "prompt_metrics": {"chars": 11861, "bytes_utf8": 11861, "lines": 396, "estimated_tokens": null}, "response_metrics": {"chars": 1788, "bytes_utf8": 1788, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 15944, "cached_input_tokens": 12032, "output_tokens": 1149, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n  SELECT\\n    \\\"ord_2\\\",\\n    CAST(\\\"id\\\" AS REAL) AS \\\"measure_value\\\",\\n    ROW_NUMBER() OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n      ORDER BY CAST(\\\"id\\\" AS REAL)\\n    ) AS \\\"rn\\\",\\n    COUNT(*) OVER (\\n      PARTITION BY \\\"ord_2\\\"\\n    ) AS \\\"cnt\\\"\\n  FROM \\\"c14\\\"\\n  WHERE \\\"ord_2\\\" IS NOT NULL\\n    AND \\\"id\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n  SELECT DISTINCT\\n    \\\"ord_2\\\",\\n    (1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n    CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n    CASE\\n      WHEN (1.0 + 0.9 * (\\\"cnt\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n        THEN CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n      ELSE CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) + 1\\n    END AS \\\"upper_rn\\\"\\n  FROM \\\"ranked\\\"\\n),\\n\\\"picked\\\" AS (\\n  SELECT\\n    p.\\\"ord_2\\\",\\n    p.\\\"pos\\\",\\n    p.\\\"lower_rn\\\",\\n    p.\\\"upper_rn\\\",\\n    MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"meas"}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/usage_summary.json

@@ -0,0 +1,20 @@
+{
+  "dataset_id": "c14",
+  "model": "v2-cli:codex",
+  "run_id": "v2q_c14_16198038f30f6c74",
+  "api_calls": 0,
+  "input_tokens": 15944,
+  "cached_input_tokens": 12032,
+  "output_tokens": 1149,
+  "total_tokens": 17093,
+  "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": 24271.67,
+  "sql_execution_elapsed_ms_total": 1221.23,
+  "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_16198038f30f6c74/cli/conversation.jsonl",
+  "note": "Executed through a local AI CLI with structured usage metadata."
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_169d7deff2a5c26c/run_manifest.json

@@ -0,0 +1,72 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T16:06:09.386236+00:00",
+  "ended_at": "2026-05-19T16:06:17.103972+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_169d7deff2a5c26c",
+    "problem_id": "v2p_c14_dec27834bf42c286",
+    "dataset_id": "c14",
+    "template_id": "tpl_m4_group_condition_rate",
+    "template_name": "Grouped Condition Rate",
+    "family_id": "conditional_dependency_structure",
+    "canonical_subitem_id": "dependency_strength_similarity",
+    "intended_facet_id": "pairwise_conditional_dependency",
+    "variant_semantic_role": "focused_target_view",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ord_0, condition_col=ord_0.",
+    "bindings": {
+      "group_col": "ord_0",
+      "condition_col": "ord_0",
+      "condition_value": "2",
+      "positive_value": "1",
+      "negative_value": "2",
+      "top_k": 15,
+      "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": 172611.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col",
+      "condition_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT {group_col},\n       AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
+    "notes": [
+      "default_facets=pairwise_conditional_dependency",
+      "template_selection_mode=rule",
+      "problem_index_within_template=5",
+      "sql_variant_index=2/2",
+      "binding_index=100"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 9,
+    "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",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_169d7deff2a5c26c/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:06:12.896599+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": 3493.31, "started_at": "2026-05-19T16:06:09.402502+00:00", "ended_at": "2026-05-19T16:06:12.895840+00:00", "prompt_metrics": {"chars": 11934, "bytes_utf8": 11934, "lines": 399, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-cc12-7973-8723-9c141298aac3\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:06:17.103819+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3204.94, "started_at": "2026-05-19T16:06:13.897639+00:00", "ended_at": "2026-05-19T16:06:17.102622+00:00", "prompt_metrics": {"chars": 11934, "bytes_utf8": 11934, "lines": 399, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-dd8a-77b0-833f-194e0723af74\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_177fd361cdb900c0/run_manifest.json

@@ -0,0 +1,67 @@
+{
+  "run_id": "v2_cli_20260502_081223_d",
+  "dataset_id": "c14",
+  "started_at": "2026-05-19T16:09:17.794239+00:00",
+  "ended_at": "2026-05-19T16:09:24.426545+00:00",
+  "status": "failed",
+  "engine": "cli",
+  "question_record": {
+    "query_record_id": "v2q_c14_177fd361cdb900c0",
+    "problem_id": "v2p_c14_7e8a197afde3a943",
+    "dataset_id": "c14",
+    "template_id": "tpl_tail_low_support_group_count_v2",
+    "template_name": "Low-Support Group Count",
+    "family_id": "tail_rarity_structure",
+    "canonical_subitem_id": "tail_set_consistency",
+    "intended_facet_id": "low_support_extremes",
+    "variant_semantic_role": "count_distribution",
+    "subitem_assignment_source": "planner_selected",
+    "source_kind": "agent",
+    "realization_mode": "agent",
+    "gate_priority": "primary",
+    "extended_family": false,
+    "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=ord_4.",
+    "bindings": {
+      "group_col": "ord_4",
+      "top_k": 17,
+      "top_n": 6,
+      "num_tiles": 10,
+      "percentile_value": 0.9,
+      "z_threshold": 2.0,
+      "fraction_threshold": 0.05,
+      "baseline_multiplier": 1.75,
+      "baseline_fraction": 0.1,
+      "min_group_size": 5,
+      "min_support": 4,
+      "measure_threshold": 4.0,
+      "time_grain": "month",
+      "lookback_rows": 3,
+      "current_period_start": "'2024-01-01'",
+      "current_period_end": "'2024-04-01'",
+      "previous_period_start": "'2023-10-01'",
+      "previous_period_end": "'2024-01-01'",
+      "drift_ratio_threshold": 0.8
+    },
+    "binding_roles": [
+      "group_col"
+    ],
+    "coverage_target_min": "5",
+    "runtime_sql_skeleton": "SELECT\n    {group_col},\n    COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
+    "notes": [
+      "default_facets=low_support_extremes",
+      "template_selection_mode=rule",
+      "problem_index_within_template=3",
+      "sql_variant_index=2/2",
+      "binding_index=122"
+    ],
+    "template_selection_mode": "rule",
+    "selected_template_rank": 11,
+    "problem_index_within_template": 3,
+    "sql_variant_index": 2,
+    "sql_variant_total": 2
+  },
+  "mode": "subitem_workload_v2",
+  "sql_source_version": "v2",
+  "sql_source_label": "v2_current",
+  "error": "AI CLI command failed with exit code 1: "
+}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_177fd361cdb900c0/trace.jsonl

@@ -0,0 +1,2 @@
+{"timestamp": "2026-05-19T16:09:20.561424+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": 2746.5, "started_at": "2026-05-19T16:09:17.813856+00:00", "ended_at": "2026-05-19T16:09:20.560393+00:00", "prompt_metrics": {"chars": 11679, "bytes_utf8": 11679, "lines": 394, "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\":\"019e40ff-abf1-7f93-8f7b-18abc555c747\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}
+{"timestamp": "2026-05-19T16:09:24.426453+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2863.06, "started_at": "2026-05-19T16:09:21.562575+00:00", "ended_at": "2026-05-19T16:09:24.425668+00:00", "prompt_metrics": {"chars": 11679, "bytes_utf8": 11679, "lines": 394, "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\":\"019e40ff-ba88-7bc3-9d19-35ad8251a3ed\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "}

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_1862c869c4ce39dc/final_answer.txt

@@ -0,0 +1,2 @@
+SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=bin_1.
+Result preview: [{"bin_1": "0", "row_count": 223018}, {"bin_1": "1", "row_count": 76982}]

Query/sql/v2/runs/v2_cli_20260502_081223_d/c14/artifacts/v2q_c14_1862c869c4ce39dc/generated_sql.sql

@@ -0,0 +1,17 @@
+-- sql_source_version: v2
+-- sql_source_label: v2_current
+-- sql_source_run_id: v2_cli_20260502_081223_d
+-- sql_source_dataset_id: c14
+-- family_id: subgroup_structure
+-- canonical_subitem_id: subgroup_size_stability
+-- intended_facet_id: subgroup_distribution_shift
+-- variant_semantic_role: count_distribution
+-- template_id: tpl_clickbench_group_count
+-- query_record_id: v2q_c14_1862c869c4ce39dc
+-- problem_id: v2p_c14_df52de0539317bbb
+-- realization_mode: agent
+-- source_kind: agent
+SELECT "bin_1", COUNT(*) AS "row_count"
+FROM "c14"
+GROUP BY "bin_1"
+ORDER BY "row_count" DESC;