{
    "action": "tool_call",
    "reasoning": "I have good evidence about rankings, physical advantages, and stance matchups. Now I need to explore the temporal/age dimension and how fights end to complete my understanding of what makes this dataset analytically rich. Let me check age effects and fight ending patterns.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT CASE WHEN f_boxer_age < 30 THEN 'Under 30' WHEN f_boxer_age BETWEEN 30 AND 35 THEN '30-35' ELSE 'Over 35' END as age_group, COUNT(*) as matches, SUM(CASE WHEN f_boxer_result = 'won' THEN 1 ELSE 0 END) as wins, ROUND(100.0 * SUM(CASE WHEN f_boxer_result = 'won' THEN 1 ELSE 0 END) / COUNT(*), 1) as win_pct, AVG(f_boxer_age) as avg_age FROM raw.cleandata WHERE f_boxer_age IS NOT NULL GROUP BY age_group ORDER BY avg_age",
        "purpose": "Understand how fighter age relates to match outcomes to assess if age/career stage is an interesting analytical dimension",
        "source": "raw"
    }
}