{
    "action": "tool_call",
    "reasoning": "I have a sample of rows from 2024 and 2020, but to identify the most interesting analytical questions, I need to understand the full dataset's scope and patterns. Let me get a comprehensive statistical overview of key dimensions: temporal coverage, country distribution, event types, medal distribution, and China's dominance pattern. This will reveal what analytical angles are most compelling.",
    "tool": "query_sql",
    "source": "raw",
    "purpose": "Get comprehensive overview statistics to identify interesting analytical angles",
    "args": {
        "sql": "SELECT COUNT(*) as total_medals, COUNT(DISTINCT year) as years_covered, MIN(year) as first_year, MAX(year) as last_year, COUNT(DISTINCT country) as countries_with_medals, COUNT(DISTINCT event) as distinct_events, SUM(CASE WHEN is_china = 1 THEN 1 ELSE 0 END) as china_medals, ROUND(100.0 * SUM(CASE WHEN is_china = 1 THEN 1 ELSE 0 END) / COUNT(*), 1) as china_percentage, COUNT(DISTINCT CASE WHEN medal = 'Gold' THEN country END) as countries_with_gold, COUNT(CASE WHEN medal = 'Gold' THEN 1 END) as total_golds, COUNT(DISTINCT era) as eras FROM raw.olympic_table_tennis_medals_1988_2024"
    }
}