{
    "action": "tool_call",
    "reasoning": "The earlier draft cited figures, but I have no tool results in evidence to back them. I'll run one profiling query over the raw table to ground the row counts, company count, date span, post-ChatGPT share, range %, volume stats and zero-volume rows before answering.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) AS total_rows, COUNT(DISTINCT company_name) AS companies, COUNT(DISTINCT stock_name) AS tickers, MIN(date) AS first_date, MAX(date) AS last_date, SUM(CASE WHEN date >= DATE '2022-11-30' THEN 1 ELSE 0 END) AS rows_post_chatgpt, ROUND(100.0 * SUM(CASE WHEN date >= DATE '2022-11-30' THEN 1 ELSE 0 END) / COUNT(*), 1) AS pct_post_chatgpt, ROUND(AVG(100.0 * (high - low) / NULLIF(close, 0)), 2) AS avg_range_pct, MEDIAN(volume) AS median_volume, ROUND(AVG(volume)) AS mean_volume, MAX(volume) AS max_volume, SUM(CASE WHEN volume = 0 THEN 1 ELSE 0 END) AS zero_volume_rows FROM raw.semi_conductor_se",
        "purpose": "Profile dataset coverage, post-ChatGPT share, range %, and volume distribution to ground the proposed analysis questions",
        "source": "raw"
    }
}