{
    "action": "tool_call",
    "reasoning": "I've seen the deal stage distribution and temporal patterns. The most striking anomaly so far is that 'Lost' deals have close_value = 0 across all 2,473 records, while 'Won' deals average $2,361. This seems counterintuitive - lost deals should still have had a proposed/expected value even if they didn't close. Let me verify this isn't a data quality issue by checking if there's a pattern to when deals were marked as lost and whether the zero values are intentional or represent missing data.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT deal_stage, COUNT(*) as total_deals, COUNT(close_value) as non_null_values, SUM(CASE WHEN close_value = 0 THEN 1 ELSE 0 END) as explicit_zeros, SUM(CASE WHEN close_value IS NULL THEN 1 ELSE 0 END) as null_values, MIN(close_value) as min_val, MAX(close_value) as max_val FROM raw.sales_pipeline GROUP BY deal_stage ORDER BY total_deals DESC",
        "purpose": "Verify whether Lost deals have explicit zero values vs nulls, and check if this pattern holds across all deal stages",
        "source": "raw"
    }
}