{
    "action": "tool_call",
    "reasoning": "No evidence is in hand for this turn, so I can't repeat the earlier data-quality claims without re-checking them. I'll run one profiling query over the key columns to ground them: uniqueness of Student_ID, nulls in the measures, ranges, and the High School students aged 19 or older.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS n_rows, COUNT(DISTINCT Student_ID) AS distinct_ids, COUNT(Student_ID) AS nonnull_ids, MIN(Student_ID) AS min_id, MAX(Student_ID) AS max_id, MIN(Age) AS min_age, MAX(Age) AS max_age, MIN(Daily_Usage_Hours) AS min_usage, MAX(Daily_Usage_Hours) AS max_usage, MIN(Weekend_Extra_Hours) AS min_wk, MAX(Weekend_Extra_Hours) AS max_wk, MIN(Sleep_Duration_Hours) AS min_sleep, MAX(Sleep_Duration_Hours) AS max_sleep, MIN(Sleep_Quality_Score) AS min_sq, MAX(Sleep_Quality_Score) AS max_sq, MIN(Perceived_Stress_Score) AS min_stress, MAX(Perceived_Stress_Score) AS max_stress, MIN(Mental_Health_Index) AS min_mh, MAX(Mental_Health_Index) AS max_mh, MIN(Academic_Performance_GPA) AS min_gpa, MAX(Academic_Performance_GPA) AS max_gpa, COUNT(*) - COUNT(Perceived_Stress_Score) AS null_stress, COUNT(*) - COUNT(Academic_Performance_GPA) AS null_gpa, COUNT(*) - COUNT(Mental_Health_Index) AS null_mh, COUNT(*) - COUNT(Sleep_Duration_Hours) AS null_sleep, SUM(CASE WHEN Daily_Usage_Hours + Sleep_Duration_Hours > 20 THEN 1 ELSE 0 END) AS time_budget_over_20, SUM(CASE WHEN Academic_Level = 'High School' AND Age >= 19 THEN 1 ELSE 0 END) AS hs_age_19_plus FROM raw.Social_media_impact_on_life",
        "purpose": "Profile uniqueness, ranges, nulls and implausible combinations in one pass",
        "source": "raw"
    }
}