{
    "action": "tool_call",
    "reasoning": "I need to understand the actual data characteristics before proposing interesting questions. Let me profile the key columns (Amount, Valuation, Industry, Date reported) to see the ranges, distributions, and variety that would support different analytical angles. I'll write one query with multiple aggregates to efficiently capture nulls, distinct counts, min/max values, and sample values.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) as total_deals, COUNT(DISTINCT Industry) as distinct_industries, COUNT(DISTINCT Company) as distinct_companies, COUNT(Amount) as non_null_amounts, COUNT(Valuation) as non_null_valuations, COUNT(\"Date reported\") as non_null_dates, COUNT(DISTINCT \"Lead investors\") as distinct_lead_investors, MIN(\"Date reported\") as earliest_date, MAX(\"Date reported\") as latest_date FROM raw.\"Largest US Venture Funding Deals Of 2023\"",
        "purpose": "Profile key columns to understand data coverage, variety, and temporal span to inform what analytical questions are feasible",
        "source": "raw"
    }
}