```json { "action": "tool_call", "reasoning": "I've identified salary_usd as the most important metric and job_title as the most important category. Now I need to query how salary varies across different job titles, showing statistics like count, average, median, min, max, and standard deviation for each role.", "tool": "query_sql", "args": { "sql": "SELECT job_title, COUNT(*) as job_count, ROUND(AVG(salary_usd), 0) as avg_salary, ROUND(MEDIAN(salary_usd), 0) as median_salary, MIN(salary_usd) as min_salary, MAX(salary_usd) as max_salary, ROUND(STDDEV(salary_usd), 0) as salary_stddev FROM raw.ai_job_dataset GROUP BY job_title ORDER BY avg_salary DESC", "purpose": "Show how the key metric (salary_usd) varies across the key category (job_title), with comprehensive statistics for each AI role", "source": "raw" } } ```