{
    "action": "tool_call",
    "reasoning": "I've inspected accounts columns. Now I need to check for data quality issues in the accounts table: outliers in revenue/employees, impossible year_established values, and any formatting inconsistencies. Let me profile these key fields.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) as total_accounts, COUNT(DISTINCT account) as distinct_accounts, MIN(revenue) as min_revenue, MAX(revenue) as max_revenue, AVG(revenue) as avg_revenue, MEDIAN(revenue) as median_revenue, STDDEV(revenue) as stddev_revenue, MIN(employees) as min_employees, MAX(employees) as max_employees, AVG(employees) as avg_employees, MEDIAN(employees) as median_employees, STDDEV(employees) as stddev_employees, MIN(year_established) as min_year, MAX(year_established) as max_year, COUNT(CASE WHEN year_established > 2024 THEN 1 END) as future_years, COUNT(CASE WHEN year_established < 1800 THEN 1 END) as very_old_years FROM raw.accounts",
        "purpose": "Profile accounts table for outliers and impossible values in revenue, employees, and year_established",
        "source": "raw"
    }
}