{
    "action": "tool_call",
    "reasoning": "I have strong evidence of natural segmentation dimensions from the results so far: result (win_A/win_B/draw), decision types (10 categories), stance matchups (orthodox vs orthodox, southpaw vs southpaw, missing), and age groups. Now I need to explore whether there are meaningful patterns in the physical attributes (height, reach, weight) and fighter records (won/lost/drawn/kos) that could provide additional segmentation dimensions. Let me check the distribution of weight classes and experience levels (based on total fights).",
    "tool": "query_sql",
    "args": {
        "sql": "WITH fighter_stats AS (SELECT weight_A AS weight, won_A + lost_A + drawn_A AS total_fights_A FROM raw.boxing_matches WHERE weight_A IS NOT NULL AND won_A IS NOT NULL UNION ALL SELECT weight_B AS weight, won_B + lost_B + drawn_B AS total_fights_B FROM raw.boxing_matches WHERE weight_B IS NOT NULL AND won_B IS NOT NULL) SELECT CASE WHEN weight < 118 THEN 'flyweight' WHEN weight < 126 THEN 'featherweight' WHEN weight < 135 THEN 'lightweight' WHEN weight < 147 THEN 'welterweight' WHEN weight < 160 THEN 'middleweight' WHEN weight < 175 THEN 'light_heavyweight' ELSE 'heavyweight' END AS weight_class, COUNT(*) AS fighter_count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 1) AS pct FROM fighter_stats GROUP BY 1 ORDER BY 2 DESC",
        "purpose": "Identify natural weight class segments",
        "source": "raw"
    }
}