{
    "action": "tool_call",
    "reasoning": "I need to examine the actual data values to identify quality issues. The evidence shows the table has a complex structure with multiple sections (day-of-week summary, daily trend, outcomes, escalation reasons, call log) all stored in one table. I can see from step-1 that all columns are VARCHAR (text), including numeric fields like 'Total Calls', 'AI Handled', etc. This is a red flag. I also see percentage values stored as text with '%' symbols. I need to query the raw data to check for: 1) impossible values (negative numbers, percentages >100%), 2) inconsistent formats (the Day column appears to mix day names, dates, section headers, and blank rows), 3) data type mismatches (numbers stored as text), and 4) any outliers in the numeric distributions. Let me start by examining the distinct values and ranges in key numeric columns.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) as total_rows, COUNT(DISTINCT Day) as distinct_days, SUM(CASE WHEN Day = '' OR Day IS NULL THEN 1 ELSE 0 END) as blank_days, SUM(CASE WHEN Day LIKE '%===%' THEN 1 ELSE 0 END) as header_rows, SUM(CASE WHEN Day IN ('Mon','Tue','Wed','Thu','Fri','Sat','Sun','Today','TOTAL') THEN 1 ELSE 0 END) as summary_rows, SUM(CASE WHEN Day LIKE '%-%' AND LENGTH(Day) <= 6 THEN 1 ELSE 0 END) as date_rows FROM raw.callyeah_analytics_2026_07_23",
        "purpose": "Count different row types to understand the mixed structure",
        "source": "raw"
    }
}