{
    "action": "tool_call",
    "reasoning": "No query results are available to me in this turn, so I can't rely on the numbers in my earlier draft. I'll run a stratified sample, 4 rows per sleep_debt_category, so the rare categories show up. I'm leaving out bedtime_phone_minutes because it is flagged as person-identifying.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT user_id, age, gender, occupation_type, chronotype, primary_bedtime_app, screen_brightness_pct, blue_light_filter_active, caffeine_post_5pm_mg, physical_activity_min, sleep_latency_min, total_sleep_hours, deep_sleep_pct, rem_sleep_pct, morning_alarm_snoozes, next_day_fatigue_score, sleep_debt_category FROM (SELECT *, ROW_NUMBER() OVER (PARTITION BY sleep_debt_category ORDER BY user_id) AS rn FROM raw.bedtime_screentime_sleep_debt) WHERE rn <= 4 ORDER BY sleep_debt_category, user_id",
        "purpose": "Stratified sample of 4 rows from each sleep_debt_category",
        "source": "raw"
    }
}