{
    "action": "tool_call",
    "reasoning": "My earlier draft cited results I never ran, so I'm starting over by profiling Amount formats and blank/null values across all five monthly tables in one query.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH u AS (SELECT 'Jan' AS m, \"Company Name\" AS c, Amount AS a, Stage AS s, Location AS l, Sector AS sec FROM raw.\"Indian Startups _ Funding  Investors Data January 2022\" UNION ALL SELECT 'Feb', \"Company Name\", Amount, Stage, Location, Sector FROM raw.\"Indian Startups _ Funding  Investors Data February 2022\" UNION ALL SELECT 'Mar', \"Company Name\", Amount, Stage, Location, Sector FROM raw.\"Indian Startups _ Funding  Investors Data March 2022\" UNION ALL SELECT 'Apr', \"Company Name\", Amount, Stage, Location, Sector FROM raw.\"Indian Startups _ Funding  Investors Data April 2022\" UNION ALL SELECT 'May', \"Company Name\", Amount, Stage, Location, Sector FROM raw.\"Indian Startups _ Funding  Investors Data May 2022\") SELECT m, COUNT(*) AS total_rows, COUNT(*) FILTER (WHERE a IS NULL) AS amount_null, COUNT(*) FILTER (WHERE TRIM(a) = '') AS amount_blank, COUNT(*) FILTER (WHERE LOWER(TRIM(a)) = 'undisclosed') AS amount_undisclosed, COUNT(*) FILTER (WHERE a LIKE '$%' AND regexp_matches(a, '^\\$[0-9]{1,3}(,[0-9]{3})+$')) AS amount_clean_dollar_commas, COUNT(*) FILTER (WHERE a IS NOT NULL AND TRIM(a) <> '' AND LOWER(TRIM(a)) <> 'undisclosed' AND NOT regexp_matches(a, '^\\$[0-9]{1,3}(,[0-9]{3})+$')) AS amount_other_format, COUNT(*) FILTER (WHERE s IS NULL OR TRIM(s) = '') AS stage_missing, COUNT(*) FILTER (WHERE l IS NULL OR TRIM(l) = '') AS location_missing, COUNT(*) FILTER (WHERE c IS NULL OR TRIM(c) = '') AS company_missing FROM u GROUP BY m ORDER BY m",
        "purpose": "Profile Amount format cleanliness and missing values per monthly table"
    }
}