{
    "action": "tool_call",
    "reasoning": "I've already inspected the columns and seen that all percentage columns are VARCHAR type with values like '1.83%' to '78.70%'. I need to examine the actual data more closely to identify quality issues. Let me check for: 1) values that don't parse as valid percentages, 2) percentages that sum incorrectly within question groups, 3) inconsistent formatting patterns, and 4) any logical impossibilities. I'll start by examining the raw percentage values across all demographic columns to look for formatting inconsistencies and outliers.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT Question, Response, Overall, \"Gender: Male\", \"Gender: Female\", \"Age: 18–29\", \"Age: 60+\", \"Income: Under $25K\", \"Income: $100K+\", \"Education: Less than HS\", \"Education: Bachelor+\" FROM raw.polling_on_ai_usage_jul_2026 WHERE Overall IN ('0.00%', '78.70%') OR \"Gender: Male\" LIKE '%-%' OR \"Gender: Female\" LIKE '%-%' OR Overall NOT LIKE '_%._%' ORDER BY CAST(REPLACE(Overall, '%', '') AS DECIMAL) DESC LIMIT 50",
        "purpose": "Identify outliers, impossible values, and formatting anomalies in percentage columns",
        "source": "raw"
    }
}