{
    "action": "tool_call",
    "reasoning": "I need to compute statistics for the numeric columns Days and Title_defenses. Both are stored as VARCHAR with mixed content (numbers, dashes, text). I'll write one query that safely extracts numeric values and computes all statistics (min, max, avg, median, stddev) for both columns together. I'll filter to only rows where the values are purely numeric (after removing commas), excluding entries with dashes, text, or other non-numeric content.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH cleaned AS (SELECT CASE WHEN Days NOT IN ('–', '−', '') AND Days NOT LIKE '%def%' AND Days NOT LIKE '%draw%' AND Days NOT LIKE '%vs%' AND Days NOT LIKE '%[%' THEN TRY_CAST(REPLACE(Days, ',', '') AS INTEGER) END as days_numeric, CASE WHEN Title_defenses NOT IN ('–', '−', '') AND Title_defenses NOT LIKE '%def%' AND Title_defenses NOT LIKE '%draw%' AND Title_defenses NOT LIKE '%vs%' AND Title_defenses NOT LIKE '%[%' THEN TRY_CAST(REPLACE(Title_defenses, ',', '') AS INTEGER) END as defenses_numeric FROM raw.championsdataset) SELECT 'Days' as column_name, COUNT(days_numeric) as valid_count, MIN(days_numeric) as min_value, MAX(days_numeric) as max_value, ROUND(AVG(days_numeric), 2) as mean_value, MEDIAN(days_numeric) as median_value, ROUND(STDDEV(days_numeric), 2) as stddev_value FROM cleaned WHERE days_numeric IS NOT NULL UNION ALL SELECT 'Title_defenses' as column_name, COUNT(defenses_numeric) as valid_count, MIN(defenses_numeric) as min_value, MAX(defenses_numeric) as max_value, ROUND(AVG(defenses_numeric), 2) as mean_value, MEDIAN(defenses_numeric) as median_value, ROUND(STDDEV(defenses_numeric), 2) as stddev_value FROM cleaned WHERE defenses_numeric IS NOT NULL",
        "purpose": "Compute min, max, mean, median, stddev for Days and Title_defenses columns, safely handling VARCHAR storage and non-numeric entries",
        "source": "raw"
    }
}