{
    "action": "tool_call",
    "reasoning": "I've confirmed no exact duplicates in the two largest tables (columns_catalog and job_logs). Now I need to check the remaining high-volume tables: llm_calls (49,360 rows), column_tags (43,853 rows), and tag_lineage_edges (42,024 rows). I'll write one query to check all three tables for exact duplicates using GROUP BY on all their columns.",
    "tool": "query_sql",
    "purpose": "Check for exact duplicate rows in llm_calls, column_tags, and tag_lineage_edges tables",
    "sql": "WITH llm_dupes AS (SELECT 'llm_calls' AS table_name, COUNT(*) AS duplicate_count FROM (SELECT call_id, COUNT(*) AS cnt FROM raw.llm_calls GROUP BY call_id, dataset_id, batch_id, job_id, purpose, model_name, prompt_tokens, completion_tokens, total_tokens, cost_usd, started_at, completed_at, duration_ms, provider, model_version, temperature, max_tokens, top_p, frequency_penalty, presence_penalty, stop_sequences, response_format HAVING COUNT(*) > 1) WHERE cnt > 1), tag_dupes AS (SELECT 'column_tags' AS table_name, COUNT(*) AS duplicate_count FROM (SELECT id, COUNT(*) AS cnt FROM raw.column_tags GROUP BY id, columns_catalog_id, tag, confidence, source, created_at, updated_at, is_active, metadata_json, created_by, updated_by, version, notes HAVING COUNT(*) > 1) WHERE cnt > 1), lineage_dupes AS (SELECT 'tag_lineage_edges' AS table_name, COUNT(*) AS duplicate_count FROM (SELECT id, COUNT(*) AS cnt FROM raw.tag_lineage_edges GROUP BY id, from_tag_id, to_tag_id, relationship_type, confidence, created_at, updated_at, is_active, metadata_json, created_by, updated_by, version, notes, weight, direction HAVING COUNT(*) > 1) WHERE cnt > 1) SELECT * FROM llm_dupes UNION ALL SELECT * FROM tag_dupes UNION ALL SELECT * FROM lineage_dupes"
}