{
    "action": "tool_call",
    "reasoning": "No evidence is visible to me in this turn, so I can't rely on earlier numbers. I'll re-check the key data-quality facts in one query: row count, distinct User_IDs, and distinct values in the categorical columns.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS total_rows, COUNT(DISTINCT User_ID) AS distinct_user_ids, COUNT(DISTINCT Gender) AS distinct_gender_labels, COUNT(DISTINCT User_Type) AS distinct_user_types, COUNT(DISTINCT Education_Level) AS distinct_education_labels, COUNT(DISTINCT AI_Tool) AS distinct_ai_tools, COUNT(DISTINCT AI_Purpose) AS distinct_ai_purposes, COUNT(DISTINCT Would_Recommend) AS distinct_recommend_labels, COUNT(DISTINCT Country) AS distinct_countries FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals",
        "purpose": "Verify row count, ID duplication and label cardinality for the data-quality summary",
        "source": "raw"
    }
}