{
    "action": "tool_call",
    "reasoning": "The evidence shows this is a CSV with mixed content: summary rows (Thu/Fri/TOTAL), section headers (=== DAILY TREND ===), and actual data rows. The columns are all VARCHAR despite containing numeric data. I need to examine the raw data structure to identify: (1) header/separator rows mixed with data, (2) type mismatches (numbers stored as text), (3) percentage formatting inconsistencies, (4) date format variations, and (5) any impossible values. Let me query a sample of rows to see the actual data patterns and identify quality issues.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT Day, \"Total Calls\", \"AI Handled\", \"Human Handled\", Voicemail, \"AI Resolution %\", \"Human %\", _unnamed_7, _unnamed_8, _unnamed_9 FROM raw.callyeah_analytics_2026_07_23 WHERE Day NOT IN ('', ' ', 'Date', 'Day', 'Outcome', 'Reason', 'TOTAL', '=== DAILY TREND — LAST 30 DAYS ===', '=== CALL OUTCOMES (30-DAY PERIOD) ===', '=== ESCALATION REASONS (30-DAY PERIOD) ===', '=== CALL LOG (LAST 150 CALLS) ===') AND \"Total Calls\" != 'Total Calls' AND \"Total Calls\" != '' LIMIT 50",
        "purpose": "Filter out header/separator rows to examine actual data rows and identify data quality issues in the numeric columns stored as VARCHAR",
        "source": "raw"
    }
}