{
    "action": "tool_call",
    "reasoning": "The dataset appears to be a formatted report with embedded headers and summary rows mixed into the data. I need to examine the actual data structure more carefully to identify quality issues. Let me query the raw data to see the actual row-level values and check for: 1) Non-numeric values in numeric columns (the inspect_columns result shows all columns are VARCHAR, which is suspicious for numeric data), 2) Header rows mixed with data, 3) Impossible values (negative counts, percentages >100%), 4) Inconsistent date formats, 5) Missing or null values in key fields.",
    "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 ('Day', 'Date', '', 'TOTAL', '=== DAILY TREND — LAST 30 DAYS ===', '=== CALL OUTCOMES (30-DAY PERIOD) ===', '=== ESCALATION REASONS (30-DAY PERIOD) ===', '=== CALL LOG (LAST 150 CALLS) ===', 'Outcome', 'Reason', 'Call ID') AND \"Total Calls\" != 'Total Calls' AND \"Total Calls\" != '' LIMIT 50",
        "purpose": "Filter out header and section divider rows to examine actual data rows and identify quality issues",
        "source": "raw"
    }
}