{
    "action": "tool_call",
    "reasoning": "The dataset has temporal axes (Date and Time columns). The gold tables include time-based aggregations by yyyy, yyyy_mm, yyyy_mm_dd, and yyyy_mm_dd_hh. To identify the overall trend, I need to query the daily aggregation table to see match counts over time. The evidence shows table_tennis_sept2022_by_Time__yyyy_mm_dd exists with row_count column. Let me query it to see the daily match volume trend.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT Time__yyyy_mm_dd, row_count FROM table_tennis_sept2022_by_Time__yyyy_mm_dd ORDER BY Time__yyyy_mm_dd",
        "purpose": "Get daily match counts to identify temporal trend",
        "source": "gold"
    }
}