{
    "action": "tool_call",
    "reasoning": "I need to examine the actual data structure more carefully. The columns I see are all VARCHAR (text) containing percentage strings like '78.70%', not numeric types. The 'Overall' column appears to be the primary aggregate metric across all demographic breakdowns. To find the highest and lowest values, I need to convert these percentage strings to numbers and then identify the extremes.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH numeric_overall AS (\n  SELECT \n    Question,\n    Response,\n    Overall,\n    CAST(REPLACE(Overall, '%', '') AS DECIMAL(10,2)) as overall_value\n  FROM raw.polling_on_ai_usage_jul_2026\n  WHERE Overall IS NOT NULL\n),\nranked AS (\n  SELECT \n    Question,\n    Response,\n    Overall,\n    overall_value,\n    ROW_NUMBER() OVER (ORDER BY overall_value DESC) as rank_desc,\n    ROW_NUMBER() OVER (ORDER BY overall_value ASC) as rank_asc\n  FROM numeric_overall\n)\nSELECT \n  Question,\n  Response,\n  Overall,\n  overall_value,\n  CASE WHEN rank_desc = 1 THEN 'Highest' ELSE 'Lowest' END as extreme_type\nFROM ranked\nWHERE rank_desc = 1 OR rank_asc = 1\nORDER BY overall_value DESC",
        "purpose": "Find the records with the highest and lowest values in the Overall metric by converting percentage strings to numeric values",
        "source": "raw"
    }
}