{
    "action": "tool_call",
    "reasoning": "From the evidence, I can see the dataset has a mixed structure with 150 individual call records, 7 daily summaries, and various metadata rows. The call records contain rich dimensions: Intent (column 'Human Handled' in the call records), Outcome (column 'Voicemail'), Date (column 'Total Calls'), Time (column 'AI Handled'), Sentiment (columns '_unnamed_8' and '_unnamed_9'). I need to analyze the actual segmentation opportunities by examining the distribution of these key dimensions in the call records. Let me query the intent types, outcomes, and sentiment distributions to identify natural groupings.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT \"Human Handled\" as intent, COUNT(*) as call_count FROM raw.callyeah_analytics_2026_07_23 WHERE \"Day\" LIKE 'CY-%' GROUP BY \"Human Handled\" ORDER BY call_count DESC",
        "purpose": "Get distribution of call intents from individual call records to identify natural segmentation by call purpose",
        "source": "raw"
    }
}