```json { "action": "tool_call", "reasoning": "The evidence shows the dataset has mixed content - some rows contain daily summaries (Thu/Fri/Sat with call counts), some contain dates (2026-07-21), and some contain metadata labels (TOTAL, Date, Count, etc.). The columns are all VARCHAR, so I need to query the actual data to understand the categorical structure. I'll query to identify which rows are actual data vs headers/totals, then analyze the categorical columns. Let me start by examining the structure more carefully to separate data rows from metadata rows.", "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 ('TOTAL', '', 'Date', 'Day') AND \"Total Calls\" NOT LIKE '2026-%' AND \"Total Calls\" != 'Total Calls' AND \"Total Calls\" != 'Count' LIMIT 50", "purpose": "Filter out header/total rows to see actual data rows and identify the categorical structure", "source": "raw" } } ```