{
    "action": "tool_call",
    "reasoning": "The evidence shows the dataset has 387K boxing matches with clear categorical dimensions (result, decision, stance) and many numeric measures. To identify natural segments, I should examine the stance matchups (orthodox vs southpaw combinations) and how physical attributes cluster. Let me first look at the stance matchup distribution since the gold tables show 3 distinct stance combinations.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT stance_A, stance_B, COUNT(*) as match_count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 1) as pct FROM raw.boxing_matches GROUP BY stance_A, stance_B ORDER BY match_count DESC",
        "purpose": "Examine stance matchup distribution to identify natural fighter-type segments",
        "source": "raw"
    }
}