{
    "action": "tool_call",
    "reasoning": "Inspect the amount outliers, nan values, malformed dates, and tiny amounts in one pass, to understand data quality before answering.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH c AS (SELECT \"Sr No\" AS sr, \"Startup Name\" AS nm, \"Date dd/mm/yyyy\" AS d, \"Amount in USD\" AS a, TRY_CAST(REPLACE(REPLACE(\"Amount in USD\", ',', ''), '+', '') AS DOUBLE) AS v FROM raw.startup_funding) SELECT 'top_amount' AS k, nm, d, a, v FROM (SELECT * FROM c WHERE v IS NOT NULL AND NOT isnan(v) AND NOT isinf(v) ORDER BY v DESC LIMIT 6) UNION ALL SELECT 'nan_or_inf' AS k, nm, d, a, v FROM (SELECT * FROM c WHERE v IS NOT NULL AND (isnan(v) OR isinf(v)) LIMIT 3) UNION ALL SELECT 'bad_date' AS k, nm, d, a, v FROM (SELECT * FROM c WHERE NOT regexp_matches(d, '^[0-9]{2}/[0-9]{2}/[0-9]{4}$') LIMIT 12) UNION ALL SELECT 'small_amount' AS k, nm, d, a, v FROM (SELECT * FROM c WHERE v IS NOT NULL AND NOT isnan(v) AND v < 10000 ORDER BY v LIMIT 5)",
        "purpose": "Find outliers, nan values, malformed dates, tiny amounts",
        "source": "raw"
    }
}