{
    "action": "tool_call",
    "reasoning": "I have good evidence on sales_pipeline nulls and deal_stage logic, and close_value distribution. Now I need to check the accounts table for outliers in revenue and employees (I have basic stats but not percentiles/outliers), and check products table for any issues. Then I'll check sales_teams and look for text format inconsistencies across key dimension fields.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT MIN(revenue) as min_rev, MAX(revenue) as max_rev, AVG(revenue) as avg_rev, PERCENTILE_CONT(0.01) WITHIN GROUP (ORDER BY revenue) as p01_rev, PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY revenue) as p99_rev, MIN(employees) as min_emp, MAX(employees) as max_emp, AVG(employees) as avg_emp, PERCENTILE_CONT(0.01) WITHIN GROUP (ORDER BY employees) as p01_emp, PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY employees) as p99_emp, COUNT(CASE WHEN revenue < 0 THEN 1 END) as negative_revenue, COUNT(CASE WHEN employees < 0 THEN 1 END) as negative_employees, COUNT(CASE WHEN year_established < 1800 OR year_established > 2024 THEN 1 END) as impossible_years FROM raw.accounts",
        "purpose": "Check accounts table for outliers and impossible values in revenue, employees, and year_established",
        "source": "raw"
    }
}