{
    "action": "tool_call",
    "reasoning": "I need to find correlations between columns. From the evidence, I can see the dataset has a mix of summary rows (Thu/Fri/etc.) and detail rows (CY-2847, etc.). The columns include call metrics (Total Calls, AI Handled, Human Handled, Voicemail) and unnamed columns (_unnamed_7, _unnamed_8, _unnamed_9) that appear to contain duration and sentiment data. I'll compute correlations between numeric columns, focusing on the detail rows where the data is granular. I need to parse the text columns into numeric values and calculate correlation coefficients.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH detail_rows AS (SELECT * FROM raw.callyeah_analytics_2026_07_23 WHERE Day LIKE 'CY-%'), parsed AS (SELECT CAST(REPLACE(REPLACE(\"Total Calls\", ',', ''), ' ', '') AS INTEGER) as total_calls, CAST(REPLACE(REPLACE(\"AI Handled\", ',', ''), ' ', '') AS INTEGER) as ai_handled, CAST(REPLACE(REPLACE(\"Human Handled\", ',', ''), ' ', '') AS INTEGER) as human_handled, CAST(REPLACE(REPLACE(Voicemail, ',', ''), ' ', '') AS INTEGER) as voicemail, CAST(_unnamed_8 AS DOUBLE) as sentiment_score FROM detail_rows WHERE \"Total Calls\" NOT LIKE '%Date%' AND \"Total Calls\" != '' AND _unnamed_8 != '' AND _unnamed_8 NOT LIKE '%Sentiment%') SELECT CORR(total_calls, ai_handled) as total_ai_corr, CORR(total_calls, human_handled) as total_human_corr, CORR(total_calls, voicemail) as total_voicemail_corr, CORR(ai_handled, human_handled) as ai_human_corr, CORR(ai_handled, sentiment_score) as ai_sentiment_corr, CORR(human_handled, sentiment_score) as human_sentiment_corr, CORR(voicemail, sentiment_score) as voicemail_sentiment_corr FROM parsed",
        "purpose": "Calculate correlation coefficients between numeric columns in the detail rows to identify strongly related variables",
        "source": "raw"
    }
}