{
    "action": "tool_call",
    "reasoning": "My earlier draft cited figures such as 822 distinct verticals and 3,041 parseable dates, and the card says ~903 distinct verticals. None of that is backed by a query I ran this turn. I'll profile the key columns in one query to ground the proposed analyses and check date quality.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS total_rows, COUNT(TRY_STRPTIME(REPLACE(\"Date dd/mm/yyyy\", '\\xc2\\xa0', ''), '%d/%m/%Y')) AS parseable_dates, MIN(TRY_STRPTIME(REPLACE(\"Date dd/mm/yyyy\", '\\xc2\\xa0', ''), '%d/%m/%Y')) AS min_date, MAX(TRY_STRPTIME(REPLACE(\"Date dd/mm/yyyy\", '\\xc2\\xa0', ''), '%d/%m/%Y')) AS max_date, COUNT(DISTINCT \"Industry Vertical\") AS distinct_verticals, COUNT(DISTINCT \"City  Location\") AS distinct_cities, COUNT(DISTINCT \"InvestmentnType\") AS distinct_round_types, COUNT(\"Amount in USD\") AS non_null_amounts, COUNT(TRY_CAST(REPLACE(\"Amount in USD\", ',', '') AS DOUBLE)) AS numeric_amounts FROM raw.startup_funding",
        "purpose": "Profile date parseability, cardinalities, and amount usability to ground suggested analyses",
        "source": "raw"
    }
}