{
    "action": "tool_call",
    "reasoning": "No tool results are visible in this context, so I can't cite the earlier numbers. I'll re-run one profiling query for nulls, ranges and key uniqueness before answering.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS n_rows, COUNT(DISTINCT Student_ID) AS distinct_ids, COUNT(Student_ID) AS ids_nonnull, COUNT(*) - COUNT(Academic_Performance_GPA) AS gpa_nulls, COUNT(*) - COUNT(Perceived_Stress_Score) AS stress_nulls, COUNT(*) - COUNT(Mental_Health_Index) AS mhi_nulls, COUNT(*) - COUNT(Sleep_Duration_Hours) AS sleep_nulls, COUNT(*) - COUNT(Daily_Usage_Hours) AS usage_nulls, MIN(Daily_Usage_Hours) AS min_usage, MAX(Daily_Usage_Hours) AS max_usage, MIN(Sleep_Duration_Hours) AS min_sleep, MAX(Sleep_Duration_Hours) AS max_sleep, MIN(Age) AS min_age, MAX(Age) AS max_age, MIN(Academic_Performance_GPA) AS min_gpa, MAX(Academic_Performance_GPA) AS max_gpa, MIN(Perceived_Stress_Score) AS min_stress, MAX(Perceived_Stress_Score) AS max_stress, MIN(Mental_Health_Index) AS min_mhi, MAX(Mental_Health_Index) AS max_mhi, SUM(CASE WHEN Daily_Usage_Hours + Sleep_Duration_Hours > 20 THEN 1 ELSE 0 END) AS usage_plus_sleep_over_20, SUM(CASE WHEN Academic_Performance_GPA = 4.0 THEN 1 ELSE 0 END) AS gpa_at_ceiling, SUM(CASE WHEN Daily_Usage_Hours = 14.0 THEN 1 ELSE 0 END) AS usage_at_max FROM raw.Social_media_impact_on_life",
        "purpose": "Profile data quality: key uniqueness, null counts, ranges, impossible combinations, ceiling pile-ups",
        "source": "raw"
    }
}