{
    "action": "tool_call",
    "reasoning": "The dataset has temporal axes (YearNum, MonthNum, WeekNum) spanning 2001-2020. To find notable spikes, dips, or breaks in the time series, I should first examine the overall volume trend. The gold table ittf_rankings_by_YearNum__yyyy_mm aggregates by year-month and will show the row count (volume) over time, which is the most direct way to spot anomalies in temporal coverage or activity.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT * FROM ittf_rankings_by_YearNum__yyyy_mm ORDER BY YearNum__yyyy_mm",
        "purpose": "Get monthly time series of ranking records to identify spikes, dips, or breaks in temporal coverage",
        "source": "gold"
    }
}