{
    "action": "tool_call",
    "reasoning": "My earlier draft cited a profiling result that isn't in the evidence I can see, so I'm re-running it as one query. It parses each text column to a number and returns one row per column with count, min, quartiles, mean, p95, max and stddev.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH p AS (SELECT TRY_CAST(Age AS DOUBLE) AS v, 'Age' AS col FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT TRY_CAST(Monthly_Income AS DOUBLE), 'Monthly_Income' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT TRY_CAST(AI_Usage_Hours_Per_Day AS DOUBLE), 'AI_Usage_Hours_Per_Day' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT TRY_CAST(Monthly_AI_Cost AS DOUBLE), 'Monthly_AI_Cost' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT Productivity_Score, 'Productivity_Score' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT CAST(Accuracy_Rating AS DOUBLE), 'Accuracy_Rating' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT CAST(Satisfaction_Score AS DOUBLE), 'Satisfaction_Score' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT TRY_CAST(Time_Saved_Hours_Per_Week AS DOUBLE), 'Time_Saved_Hours_Per_Week' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals UNION ALL SELECT TRY_CAST(Work_or_Study_Hours_Per_Day AS DOUBLE), 'Work_or_Study_Hours_Per_Day' FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals) SELECT col, COUNT(v) AS n_valid, COUNT(*) - COUNT(v) AS n_missing, MIN(v) AS min_v, quantile_cont(v, 0.25) AS p25, MEDIAN(v) AS median_v, AVG(v) AS mean_v, quantile_cont(v, 0.75) AS p75, quantile_cont(v, 0.95) AS p95, MAX(v) AS max_v, STDDEV(v) AS stddev_v FROM p GROUP BY col ORDER BY col",
        "purpose": "Distribution summary (min, quartiles, mean, p95, max, stddev, missing) for the nine numeric columns",
        "source": "raw"
    }
}