{
    "action": "tool_call",
    "reasoning": "Compute correlations among usage and wellbeing measures in one query to check for relationships, including any counterintuitive ones.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT corr(Daily_Usage_Hours, Sleep_Duration_Hours) AS usage_sleep, corr(Daily_Usage_Hours, Mental_Health_Index) AS usage_mh, corr(Daily_Usage_Hours, Perceived_Stress_Score) AS usage_stress, corr(Daily_Usage_Hours, Academic_Performance_GPA) AS usage_gpa, corr(Daily_Usage_Hours, Sleep_Quality_Score) AS usage_sleepq, corr(Sleep_Duration_Hours, Mental_Health_Index) AS sleep_mh, corr(Perceived_Stress_Score, Mental_Health_Index) AS stress_mh, corr(Academic_Performance_GPA, Mental_Health_Index) AS gpa_mh, corr(Weekend_Extra_Hours, Daily_Usage_Hours) AS wk_daily, corr(Age, Academic_Performance_GPA) AS age_gpa, COUNT(*) AS n FROM raw.Social_media_impact_on_life",
        "purpose": "Check correlations among usage and wellbeing measures for counterintuitive relationships",
        "source": "raw"
    }
}