{
    "action": "tool_call",
    "reasoning": "No evidence from this turn is available, so I can't cite the earlier numbers. I'll rebuild the monthly comparison from the raw tables, starting with row counts and the Amount text formats.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH u AS (SELECT 'Jan' AS m, 1 AS o, \"Company Name\" AS c, Amount AS a FROM raw.\"Indian Startups _ Funding  Investors Data January 2022\" UNION ALL SELECT 'Feb',2,\"Company Name\",Amount FROM raw.\"Indian Startups _ Funding  Investors Data February 2022\" UNION ALL SELECT 'Mar',3,\"Company Name\",Amount FROM raw.\"Indian Startups _ Funding  Investors Data March 2022\" UNION ALL SELECT 'Apr',4,\"Company Name\",Amount FROM raw.\"Indian Startups _ Funding  Investors Data April 2022\" UNION ALL SELECT 'May',5,\"Company Name\",Amount FROM raw.\"Indian Startups _ Funding  Investors Data May 2022\") SELECT m, o, COUNT(*) AS rows_total, COUNT(c) AS rows_with_company, COUNT(a) AS rows_with_amount, COUNT(*) FILTER (WHERE TRY_CAST(REPLACE(REPLACE(a,'$',''),',','') AS DOUBLE) IS NOT NULL) AS parseable_amount, MIN(a) AS min_text, MAX(a) AS max_text FROM u GROUP BY m, o ORDER BY o",
        "purpose": "Monthly row counts and Amount parseability to ground the trend answer",
        "source": "raw"
    }
}