{
    "action": "tool_call",
    "reasoning": "No evidence for the correlation claims is available in this turn, so I'll compute them with one SQL query. It covers caffeine, phone minutes, activity, brightness and the blue-light filter against the sleep outcomes.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS n, corr(caffeine_post_5pm_mg, total_sleep_hours) AS caff_sleep_hours, corr(caffeine_post_5pm_mg, deep_sleep_pct) AS caff_deep, corr(caffeine_post_5pm_mg, sleep_latency_min) AS caff_latency, corr(caffeine_post_5pm_mg, next_day_fatigue_score) AS caff_fatigue, corr(bedtime_phone_minutes, sleep_latency_min) AS phone_latency, corr(bedtime_phone_minutes, next_day_fatigue_score) AS phone_fatigue, corr(bedtime_phone_minutes, total_sleep_hours) AS phone_sleep_hours, corr(physical_activity_min, total_sleep_hours) AS act_sleep_hours, corr(physical_activity_min, next_day_fatigue_score) AS act_fatigue, corr(screen_brightness_pct, sleep_latency_min) AS bright_latency, corr(blue_light_filter_active, sleep_latency_min) AS filter_latency, corr(blue_light_filter_active, total_sleep_hours) AS filter_sleep_hours FROM raw.bedtime_screentime_sleep_debt",
        "purpose": "Compute correlations of caffeine, phone use, activity, brightness and blue-light filter with sleep outcomes",
        "source": "raw"
    }
}