{
    "action": "tool_call",
    "reasoning": "My earlier draft cited a 15-row sample, but I have no query result in this context to back it. I'll run one profile query for row counts, null counts and distinct counts across the key columns to ground the data-quality findings.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS n_rows, COUNT(DISTINCT User_ID) AS distinct_users, COUNT(Age) AS age_nonnull, COUNT(Gender) AS gender_nonnull, COUNT(DISTINCT Gender) AS gender_distinct, COUNT(Education_Level) AS edu_nonnull, COUNT(DISTINCT Education_Level) AS edu_distinct, COUNT(Profession) AS prof_nonnull, COUNT(AI_Tool) AS tool_nonnull, COUNT(DISTINCT AI_Tool) AS tool_distinct, COUNT(AI_Purpose) AS purpose_nonnull, COUNT(Tasks_Performed) AS tasks_nonnull, COUNT(Productivity_Score) AS prod_nonnull, COUNT(Accuracy_Rating) AS acc_nonnull, COUNT(Satisfaction_Score) AS sat_nonnull, COUNT(Would_Recommend) AS rec_nonnull, COUNT(DISTINCT Would_Recommend) AS rec_distinct, COUNT(Monthly_Income) AS income_nonnull, COUNT(Monthly_AI_Cost) AS cost_nonnull FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals",
        "purpose": "Profile completeness and label cardinality across the dataset",
        "source": "raw"
    }
}