{
    "action": "tool_call",
    "reasoning": "The evidence shows this dataset has a mixed structure: some rows are daily summaries (Thu, Fri, Sat, etc.) and others are individual call records (CY-2847, CY-2848, etc.). I need to understand the full distribution of record types and identify the natural segmentation. Let me query to see how many rows fall into each category: summary rows vs. individual call records vs. header/metadata rows.",
    "tool": "query_sql",
    "sql": "SELECT CASE WHEN Day IN ('Thu', 'Fri', 'Sat', 'Sun', 'Mon', 'Tue', 'Wed', 'Today', 'Yesterday') THEN 'Daily Summary' WHEN Day LIKE 'CY-%' THEN 'Individual Call Record' WHEN Day = 'TOTAL' THEN 'Aggregate Total' WHEN Day LIKE '%-%' AND LENGTH(Day) <= 6 THEN 'Date Value' WHEN Day = '' OR Day IS NULL THEN 'Blank/Empty' WHEN Day LIKE '%===%' OR Day LIKE 'Call ID%' THEN 'Header/Metadata' ELSE 'Other' END AS record_type, COUNT(*) AS count FROM raw.callyeah_analytics_2026_07_23 GROUP BY record_type ORDER BY count DESC",
    "purpose": "Identify the natural segmentation of records by categorizing the Day field values into logical groups"
}