```json { "action": "tool_call", "reasoning": "The dataset has mixed structure with summary rows and detail rows. I need to identify which rows contain actual categorical data vs aggregates/headers. From the evidence, I see the 'Day' column contains dates (23-Jun, 24-Jun, etc.), day names (Thu, Fri, etc.), section headers (=== DAILY TREND...), and aggregate labels (TOTAL, AI Resolved, etc.). The 'Voicemail' column appears to contain call topics/reasons. I should query to get the most common values for the main categorical columns, filtering out header/aggregate rows. Let me get the top values for Day (filtering to actual dates/day names), and the categorical content in Voicemail and any other text columns that contain meaningful categories.", "tool": "query_sql", "args": { "sql": "SELECT 'Day' as column_name, Day as value, COUNT(*) as frequency FROM raw.callyeah_analytics_2026_07_23 WHERE Day NOT LIKE '===%' AND Day != 'TOTAL' AND Day != '' AND Day NOT LIKE 'CY-%' AND Day NOT IN ('AI Resolved', 'Human Handled', 'Voicemail', 'Abandoned', 'Date', 'Call ID', 'Caller requested agent', 'Complex dispute', 'Language-based escalation', 'AI confidence threshold', 'Emotional distress detected', 'Out-of-scope request') GROUP BY Day ORDER BY frequency DESC, Day LIMIT 15", "purpose": "Get the most common Day values (actual dates and day names) excluding headers and aggregate rows" } } ```