{
    "action": "tool_call",
    "reasoning": "I've seen the deal stage distribution and value patterns. The most striking finding so far is that Lost deals have close_value = 0 across all 2,473 records, which is unusual—typically lost deals would retain their proposed value for analysis. But before declaring this the most surprising finding, I should explore other potential anomalies: (1) the temporal patterns—do Won/Lost deals cluster in unexpected ways? (2) account/product concentration—is there extreme skew? (3) sales agent performance variance. Let me check the temporal distribution of Won vs Lost deals to see if there's a counterintuitive pattern in when deals close.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT DATE_TRUNC('month', close_date) AS month, deal_stage, COUNT(*) AS deals, SUM(close_value) AS total_value FROM raw.sales_pipeline WHERE deal_stage IN ('Won', 'Lost') GROUP BY 1, 2 ORDER BY 1, 2",
        "purpose": "Examine temporal distribution of Won vs Lost deals to identify any counterintuitive patterns in closure timing",
        "source": "raw"
    }
}