```json { "action": "tool_call", "reasoning": "The evidence shows the dataset has mixed structure - some rows are daily summaries (Thu/Fri/Sat etc.), some are date-based (23-Jun, 24-Jun), and some are section headers or call-level records. I need to understand the actual categorical columns and their distributions. The inspect_columns output shows column names but the 'range' values are confusing (e.g., Day ranges from '..Voicemail'). Let me query the actual distinct values and their frequencies for the key categorical columns to understand what this dataset really contains.", "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 IS NOT NULL AND Day != '' GROUP BY Day ORDER BY frequency DESC, Day LIMIT 20", "purpose": "Get the most common values in the Day column to understand its categorical distribution", "source": "raw" } } ```