```json { "action": "tool_call", "reasoning": "The evidence shows this dataset contains mixed record types: 150 individual call records, 30 date values, 13 'Other', 8 blank rows, 7 daily summaries, 5 headers, and 3 aggregate totals. The individual call records have rich attributes (Intent, Outcome, Sentiment) that could provide natural segmentation. I need to analyze the call-level data to identify the most meaningful grouping dimensions. Let me query the Intent and Outcome distributions from the call records.", "tool": "query_sql", "args": { "sql": "SELECT \"Total Calls\" AS intent, COUNT(*) AS call_count FROM raw.callyeah_analytics_2026_07_23 WHERE Day LIKE 'CY-%' GROUP BY \"Total Calls\" ORDER BY call_count DESC", "purpose": "Get distribution of call intents from individual call records to identify natural segmentation by customer need" } } ```