{
    "action": "tool_call",
    "reasoning": "My earlier reply was prose with no tool result behind it in this context, so I can't cite its numbers. I'll re-run one distinct-count query across all five monthly tables to get grounded figures.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT 'January' AS month, COUNT(*) AS n_rows, COUNT(\"Company Name\") AS n_company, COUNT(DISTINCT \"Company Name\") AS d_company, COUNT(DISTINCT Location) AS d_location, COUNT(DISTINCT Sector) AS d_sector, COUNT(DISTINCT Stage) AS d_stage, COUNT(DISTINCT Investor) AS d_investor FROM raw.\"Indian Startups _ Funding  Investors Data January 2022\" UNION ALL SELECT 'February', COUNT(*), COUNT(\"Company Name\"), COUNT(DISTINCT \"Company Name\"), COUNT(DISTINCT Location), COUNT(DISTINCT Sector), COUNT(DISTINCT Stage), COUNT(DISTINCT Investor) FROM raw.\"Indian Startups _ Funding  Investors Data February 2022\" UNION ALL SELECT 'March', COUNT(*), COUNT(\"Company Name\"), COUNT(DISTINCT \"Company Name\"), COUNT(DISTINCT Location), COUNT(DISTINCT Sector), COUNT(DISTINCT Stage), COUNT(DISTINCT Investor) FROM raw.\"Indian Startups _ Funding  Investors Data March 2022\" UNION ALL SELECT 'April', COUNT(*), COUNT(\"Company Name\"), COUNT(DISTINCT \"Company Name\"), COUNT(DISTINCT Location), COUNT(DISTINCT Sector), COUNT(DISTINCT Stage), COUNT(DISTINCT Investor) FROM raw.\"Indian Startups _ Funding  Investors Data April 2022\" UNION ALL SELECT 'May', COUNT(*), COUNT(\"Company Name\"), COUNT(DISTINCT \"Company Name\"), COUNT(DISTINCT Location), COUNT(DISTINCT Sector), COUNT(DISTINCT Stage), COUNT(DISTINCT Investor) FROM raw.\"Indian Startups _ Funding  Investors Data May 2022\"",
        "purpose": "Per-table row counts, non-null company names, and distinct counts for key columns across the five monthly tables",
        "source": "raw"
    }
}