{
    "action": "tool_call",
    "reasoning": "The evidence from earlier steps is not visible to me now, so I will re-ground the data-quality findings in one profiling query before answering: nulls, invalid prices, zero volume, duplicate keys, and cardinality.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS n_rows, COUNT(DISTINCT stock_name) AS n_stocks, COUNT(DISTINCT company_name) AS n_companies, COUNT(*) - COUNT(DISTINCT (stock_name || '|' || CAST(date AS VARCHAR))) AS duplicate_key_rows, SUM(CASE WHEN open IS NULL OR high IS NULL OR low IS NULL OR close IS NULL OR volume IS NULL OR date IS NULL THEN 1 ELSE 0 END) AS rows_with_nulls, SUM(CASE WHEN high < low THEN 1 ELSE 0 END) AS high_lt_low, SUM(CASE WHEN close > high OR close < low OR open > high OR open < low THEN 1 ELSE 0 END) AS open_close_outside_range, SUM(CASE WHEN open <= 0 OR high <= 0 OR low <= 0 OR close <= 0 THEN 1 ELSE 0 END) AS nonpositive_prices, SUM(CASE WHEN volume = 0 THEN 1 ELSE 0 END) AS zero_volume_rows, SUM(CASE WHEN volume < 0 THEN 1 ELSE 0 END) AS negative_volume_rows, SUM(CASE WHEN high = low THEN 1 ELSE 0 END) AS flat_range_rows, MIN(date) AS min_date, MAX(date) AS max_date FROM raw.semi_conductor_se",
        "purpose": "Single-pass data-quality profile: nulls, duplicates, price-range violations, zero/negative volume",
        "source": "raw"
    }
}