{
    "action": "tool_call",
    "reasoning": "I need to profile the dataset's key dimensions and measures to understand what analytical questions it can support. I'll examine temporal coverage, salary distribution, job title/company/industry diversity, and geographic spread.",
    "tool": "query_sql",
    "sql": "SELECT COUNT(*) as total_jobs, MIN(posting_date) as earliest_posting, MAX(posting_date) as latest_posting, MIN(application_deadline) as earliest_deadline, MAX(application_deadline) as latest_deadline, COUNT(DISTINCT job_title) as distinct_job_titles, COUNT(DISTINCT company_name) as distinct_companies, COUNT(DISTINCT industry) as distinct_industries, COUNT(DISTINCT company_location) as distinct_locations, COUNT(DISTINCT employee_residence) as distinct_residences, MIN(salary_usd) as min_salary, MAX(salary_usd) as max_salary, MEDIAN(salary_usd) as median_salary, AVG(salary_usd) as avg_salary, MIN(years_experience) as min_experience, MAX(years_experience) as max_experience, MEDIAN(years_experience) as median_experience, COUNT(DISTINCT remote_ratio) as remote_options, COUNT(DISTINCT experience_level) as experience_levels, COUNT(DISTINCT education_required) as education_levels FROM raw.ai_job_dataset",
    "purpose": "Profile key dimensions to understand what analytical questions the dataset can support"
}