{
    "action": "tool_call",
    "reasoning": "I have no executed evidence in this turn, and the numbers in my previous draft are not backed by any tool result. I'll profile the Amount formats across all five tables with one query before answering.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH u AS (SELECT 'January' AS month, Amount FROM raw.\"Indian Startups _ Funding  Investors Data January 2022\" UNION ALL SELECT 'February', Amount FROM raw.\"Indian Startups _ Funding  Investors Data February 2022\" UNION ALL SELECT 'March', Amount FROM raw.\"Indian Startups _ Funding  Investors Data March 2022\" UNION ALL SELECT 'April', Amount FROM raw.\"Indian Startups _ Funding  Investors Data April 2022\" UNION ALL SELECT 'May', Amount FROM raw.\"Indian Startups _ Funding  Investors Data May 2022\") SELECT month, COUNT(*) AS total_rows, COUNT(*) FILTER (WHERE Amount IS NULL OR TRIM(Amount) = '') AS blank, COUNT(*) FILTER (WHERE LOWER(TRIM(Amount)) = 'undisclosed') AS undisclosed, COUNT(*) FILTER (WHERE regexp_matches(TRIM(Amount), '^\\$[0-9]{1,3}(,[0-9]{3})+$')) AS clean_dollar_commas, COUNT(*) FILTER (WHERE regexp_matches(TRIM(Amount), '^[0-9]{1,3}(,[0-9]{3})+$')) AS no_dollar_commas, COUNT(*) FILTER (WHERE NOT (Amount IS NULL OR TRIM(Amount) = '' OR LOWER(TRIM(Amount)) = 'undisclosed' OR regexp_matches(TRIM(Amount), '^\\$[0-9]{1,3}(,[0-9]{3})+$') OR regexp_matches(TRIM(Amount), '^[0-9]{1,3}(,[0-9]{3})+$'))) AS other_formats FROM u GROUP BY month ORDER BY month",
        "purpose": "Profile Amount text formats per monthly table",
        "source": "raw"
    }
}