{
    "action": "tool_call",
    "reasoning": "I need to examine the actual data values more systematically to identify quality issues. From the evidence so far, I can see that the 'Days' column contains mixed content (numbers like '1', '2', '13' alongside text like 'def.' and full descriptions like 'def. Daniel Eduardo Neto on December 16, 1989'). I should query the raw data to examine patterns across all key columns, looking for: 1) mixed data types in numeric columns, 2) placeholder values like '–' and '−', 3) inconsistent date formats, 4) outliers in numeric fields. Let me start by examining the distinct values and patterns in the problematic columns I've already identified.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT Days, COUNT(*) as count FROM raw.championsdataset GROUP BY Days ORDER BY count DESC LIMIT 30",
        "purpose": "Get full distribution of Days column values to identify all quality issues",
        "source": "raw"
    }
}