{
    "action": "tool_call",
    "reasoning": "I have strong evidence on temporal, geographic, style, product, and ABV segmentation. To complete the picture, I should profile user engagement tiers (power users vs casual raters) since the users table shows activity ranging from 1 to 83,346 total activities. This will reveal whether there's a natural user segmentation by engagement level.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT CASE WHEN total_activity_count = 1 THEN '1. Single rating' WHEN total_activity_count BETWEEN 2 AND 10 THEN '2. Casual (2-10)' WHEN total_activity_count BETWEEN 11 AND 50 THEN '3. Regular (11-50)' WHEN total_activity_count BETWEEN 51 AND 200 THEN '4. Active (51-200)' WHEN total_activity_count BETWEEN 201 AND 1000 THEN '5. Enthusiast (201-1K)' ELSE '6. Power user (1K+)' END AS engagement_tier, COUNT(*) AS user_count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) AS pct_of_users, MIN(total_activity_count) AS min_activities, MAX(total_activity_count) AS max_activities FROM raw.users GROUP BY 1 ORDER BY min_activities",
        "purpose": "Profile user engagement distribution to identify natural user segmentation tiers",
        "source": "raw"
    }
}