{
    "action": "tool_call",
    "reasoning": "My earlier draft cited numbers with no tool result behind them in this context, so I'm discarding it. First I'll compute monthly deal counts and amount completeness from the raw tables, so any claim about the trend rests on executed SQL.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT 'January' AS month, 1 AS m, COUNT(*) AS rows_n, COUNT(\"Company Name\") AS named, COUNT(Amount) AS amount_present, SUM(CASE WHEN lower(Amount) LIKE '%undisclosed%' THEN 1 ELSE 0 END) AS undisclosed FROM raw.\"Indian Startups _ Funding  Investors Data January 2022\" UNION ALL SELECT 'February', 2, COUNT(*), COUNT(\"Company Name\"), COUNT(Amount), SUM(CASE WHEN lower(Amount) LIKE '%undisclosed%' THEN 1 ELSE 0 END) FROM raw.\"Indian Startups _ Funding  Investors Data February 2022\" UNION ALL SELECT 'March', 3, COUNT(*), COUNT(\"Company Name\"), COUNT(Amount), SUM(CASE WHEN lower(Amount) LIKE '%undisclosed%' THEN 1 ELSE 0 END) FROM raw.\"Indian Startups _ Funding  Investors Data March 2022\" UNION ALL SELECT 'April', 4, COUNT(*), COUNT(\"Company Name\"), COUNT(Amount), SUM(CASE WHEN lower(Amount) LIKE '%undisclosed%' THEN 1 ELSE 0 END) FROM raw.\"Indian Startups _ Funding  Investors Data April 2022\" UNION ALL SELECT 'May', 5, COUNT(*), COUNT(\"Company Name\"), COUNT(Amount), SUM(CASE WHEN lower(Amount) LIKE '%undisclosed%' THEN 1 ELSE 0 END) FROM raw.\"Indian Startups _ Funding  Investors Data May 2022\" ORDER BY m",
        "purpose": "Monthly funding-round counts and Amount completeness across Jan-May 2022",
        "source": "raw"
    }
}