{
    "action": "tool_call",
    "reasoning": "The question asks for correlations and relationships between columns. The dataset card shows no validated foreign keys, but the evidence confirms there are business keys that could connect tables (account names, product codes, sales agents). I need to: 1) Check numeric correlations within tables (revenue/employees in accounts, close_value/engage_date in sales_pipeline), 2) Examine categorical relationships (deal_stage vs close_value, product vs sales_price), and 3) Verify the business key overlaps mentioned in the insight. I'll start by profiling numeric columns across all tables to compute correlation coefficients.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT CORR(revenue, employees) as revenue_employees_corr, CORR(year_established, revenue) as year_revenue_corr, CORR(year_established, employees) as year_employees_corr FROM raw.accounts WHERE revenue IS NOT NULL AND employees IS NOT NULL",
        "purpose": "Calculate correlations between numeric measures in accounts table",
        "source": "raw"
    }
}