```json { "action": "tool_call", "reasoning": "The question asks for a classification of all columns across the dataset. The dataset card shows 5 tables with 12+11+7+7+7=44 total columns. Rather than calling inspect_columns on each table separately (5 calls), I can query the analytics.column_overview metadata table once to get the semantic_role, rough_kind, and aggregation_role for all columns across all tables. This metadata table contains exactly the classification information needed: semantic_role indicates identifier/dimension/measure, rough_kind shows categorical/numeric/temporal types, and key_role/aggregation_role provide additional context.", "tool": "query_sql", "args": { "sql": "SELECT table_name, column_name, phys_type, semantic_role, rough_kind, aggregation_role, key_role, coordinate FROM analytics.column_overview ORDER BY table_name, column_name", "purpose": "Get semantic classification (identifier/dimension/metric/temporal) for all columns across all tables", "source": "raw" } } ```