{
    "action": "tool_call",
    "reasoning": "I need to understand the dataset's key dimensions and patterns to identify the most interesting analytical questions. Let me start by profiling the core dimensions: temporal coverage, country distribution, event types, and China's dominance pattern. This will reveal what analytical angles are most compelling.",
    "tool": "query_sql",
    "purpose": "Profile key dimensions 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, COUNT(DISTINCT event) as 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_pct, COUNT(DISTINCT CASE WHEN medal = 'Gold' THEN country END) as gold_medal_countries FROM raw.olympic_table_tennis_medals_1988_2024",
        "source": "raw"
    }
}