{
    "action": "tool_call",
    "reasoning": "The previous query failed because min_value and max_value are stored as VARCHAR in the metadata, not as numeric types. I need to query the actual data tables to compute proper numeric statistics. I'll write a query that computes min, max, mean, median, and spread for all numeric columns across the key tables. Since there are many tables, I'll focus on the main aggregated scores table and a representative sample of play tables to demonstrate the distribution patterns.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT 'AwayScore' AS column_name, MIN(AwayScore) AS min_val, MAX(AwayScore) AS max_val, AVG(AwayScore) AS mean_val, MEDIAN(AwayScore) AS median_val, MAX(AwayScore) - MIN(AwayScore) AS spread, COUNT(*) AS total_rows, COUNT(AwayScore) AS non_null_rows FROM raw.2010_2026_scores UNION ALL SELECT 'HomeScore', MIN(HomeScore), MAX(HomeScore), AVG(HomeScore), MEDIAN(HomeScore), MAX(HomeScore) - MIN(HomeScore), COUNT(*), COUNT(HomeScore) FROM raw.2010_2026_scores UNION ALL SELECT 'Season', MIN(Season), MAX(Season), AVG(Season), MEDIAN(Season), MAX(Season) - MIN(Season), COUNT(*), COUNT(Season) FROM raw.2010_2026_scores",
        "purpose": "Compute distribution statistics (min, max, mean, median, spread) for numeric columns in the main scores table",
        "source": "raw"
    }
}