I need to compute distribution statistics (min, max, mean, median, and spread) for all numeric columns in the dataset. The evidence so far shows min/max/avg for the first 50 columns, but I need median and a measure of spread (standard deviation), and I need to cover all numeric columns, not just the first 50. Let me write a comprehensive query that computes these statistics for all numeric columns across all tables. ```json { "action": "tool_call", "reasoning": "The evidence shows basic stats for 50 columns, but I need median, standard deviation (spread), and coverage of ALL numeric columns. I'll query the columns_catalog and related metadata to build a complete distribution summary with min, max, mean, median, and stddev for every numeric column in the dataset.", "tool": "query_sql", "args": { "sql": "WITH numeric_cols AS (SELECT t.table_name, c.column_name, c.phys_type FROM raw.tables_catalog t JOIN raw.columns_catalog c ON t.id = c.tables_catalog_id WHERE c.phys_type IN ('BIGINT', 'DOUBLE', 'DECIMAL', 'INTEGER', 'FLOAT', 'REAL')) SELECT table_name, column_name, phys_type, COUNT(*) as column_count FROM numeric_cols GROUP BY table_name, column_name, phys_type ORDER BY table_name, column_name LIMIT 50", "purpose": "First, identify all numeric columns across all tables to understand the scope before computing distribution statistics" } } ```