```json { "action": "tool_call", "reasoning": "I have missing value data for popular_matches from step-0, but I need to check the fighters table as well to provide a complete answer about all columns with missing values across the entire dataset.", "tool": "query_sql", "args": { "sql": "SELECT 'fighters' as table_name, column_name, COUNT(*) - COUNT(column_name) as null_count, COUNT(*) as total_rows, ROUND(100.0 * (COUNT(*) - COUNT(column_name)) / COUNT(*), 2) as missing_percentage FROM (SELECT name, wins, looses, draws, ko_rate, stance, age, height, reach, country FROM raw.fighters) UNPIVOT (column_name FOR col IN (name, wins, looses, draws, ko_rate, stance, age, height, reach, country)) GROUP BY column_name HAVING null_count > 0 ORDER BY missing_percentage DESC", "purpose": "Check for missing values in the fighters table to complete the analysis of missing data across all tables", "source": "raw" } } ```