```json { "action": "tool_call", "reasoning": "The user wants distribution statistics (min, max, mean, median, spread) for all numeric columns. From the evidence, I can see the numeric columns are: match_number, team1_runs, team1_wickets, team2_runs, team2_wickets, win_by_runs, win_by_wickets, overs_limit, balls_per_over. I'll write ONE query with all aggregates for all these columns to efficiently compute the statistics in a single pass.", "tool": "query_sql", "args": { "sql": "SELECT COUNT(*) as total_rows, COUNT(match_number) as match_number_non_null, MIN(match_number) as match_number_min, MAX(match_number) as match_number_max, AVG(match_number) as match_number_mean, MEDIAN(match_number) as match_number_median, STDDEV(match_number) as match_number_stddev, MIN(team1_runs) as team1_runs_min, MAX(team1_runs) as team1_runs_max, AVG(team1_runs) as team1_runs_mean, MEDIAN(team1_runs) as team1_runs_median, STDDEV(team1_runs) as team1_runs_stddev, MIN(team1_wickets) as team1_wickets_min, MAX(team1_wickets) as team1_wickets_max, AVG(team1_wickets) as team1_wickets_mean, MEDIAN(team1_wickets) as team1_wickets_median, STDDEV(team1_wickets) as team1_wickets_stddev, MIN(team2_runs) as team2_runs_min, MAX(team2_runs) as team2_runs_max, AVG(team2_runs) as team2_runs_mean, MEDIAN(team2_runs) as team2_runs_median, STDDEV(team2_runs) as team2_runs_stddev, MIN(team2_wickets) as team2_wickets_min, MAX(team2_wickets) as team2_wickets_max, AVG(team2_wickets) as team2_wickets_mean, MEDIAN(team2_wickets) as team2_wickets_median, STDDEV(team2_wickets) as team2_wickets_stddev, MIN(win_by_runs) as win_by_runs_min, MAX(win_by_runs) as win_by_runs_max, AVG(win_by_runs) as win_by_runs_mean, MEDIAN(win_by_runs) as win_by_runs_median, STDDEV(win_by_runs) as win_by_runs_stddev, MIN(win_by_wickets) as win_by_wickets_min, MAX(win_by_wickets) as win_by_wickets_max, AVG(win_by_wickets) as win_by_wickets_mean, MEDIAN(win_by_wickets) as win_by_wickets_median, STDDEV(win_by_wickets) as win_by_wickets_stddev, MIN(overs_limit) as overs_limit_min, MAX(overs_limit) as overs_limit_max, AVG(overs_limit) as overs_limit_mean, MEDIAN(overs_limit) as overs_limit_median, STDDEV(overs_limit) as overs_limit_stddev, MIN(balls_per_over) as balls_per_over_min, MAX(balls_per_over) as balls_per_over_max, AVG(balls_per_over) as balls_per_over_mean, MEDIAN(balls_per_over) as balls_per_over_median, STDDEV(balls_per_over) as balls_per_over_stddev FROM raw.IPL_Matches_Data_2008_2026", "purpose": "Compute distribution statistics (min, max, mean, median, stddev) for all numeric columns in one query", "source": "raw" } } ```