Looking at the evidence, I can see this is a call center operations dataset tracking AI vs. human call handling across days of the week. The data shows daily metrics for total calls, AI-handled calls, human-handled calls, voicemail, and resolution percentages. Let me explore the full temporal range and data structure to identify the most interesting analytical questions: ```json { "action": "tool_call", "reasoning": "I need to understand the complete temporal coverage and data patterns. The sample shows days of the week plus 'TOTAL' and 'Today' rows, but I need to see the full date range and whether there are multiple weeks of data to identify trend-based questions.", "tool": "query_sql", "args": { "sql": "SELECT MIN(Day) as earliest_day, MAX(Day) as latest_day, COUNT(*) as total_records, COUNT(DISTINCT Day) as distinct_days, COUNT(CASE WHEN Day IN ('Mon','Tue','Wed','Thu','Fri','Sat','Sun','Today','TOTAL') THEN 1 END) as day_name_records, COUNT(CASE WHEN Day NOT IN ('Mon','Tue','Wed','Thu','Fri','Sat','Sun','Today','TOTAL','') THEN 1 END) as date_records FROM raw.callyeah_analytics_2026_07_23 WHERE Day IS NOT NULL AND Day != ''", "purpose": "Understand the temporal structure and whether data contains actual dates or just day-of-week summaries", "source": "raw" } } ```