{
    "action": "tool_call",
    "reasoning": "I need to explore stance matchups since the dataset has stance_A and stance_B dimensions. The gold tables include stance-based aggregations, which suggests this is a rich analytical dimension. Let me check the actual stance matchup patterns and their win rates to see if this reveals interesting dynamics (orthodox vs southpaw advantages).",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT stance_A, stance_B, COUNT(*) as matches, SUM(CASE WHEN result = 'win_A' THEN 1 ELSE 0 END) as a_wins, SUM(CASE WHEN result = 'win_B' THEN 1 ELSE 0 END) as b_wins, SUM(CASE WHEN result = 'draw' THEN 1 ELSE 0 END) as draws, ROUND(100.0 * SUM(CASE WHEN result = 'win_A' THEN 1 ELSE 0 END) / COUNT(*), 2) as a_win_pct FROM raw.boxing_matches GROUP BY stance_A, stance_B ORDER BY matches DESC",
        "purpose": "Analyze stance matchup dynamics (orthodox vs southpaw) to see if certain combinations show meaningful win rate differences",
        "source": "raw"
    }
}