| name | analytics-balance |
| description | Extract analytics and game balance entities from narrative text. Use when analyzing player metrics, difficulty curves, drop rates, loot tables, heatmaps, and balance tuning. |
analytics-balance
Domain skill for Analytics Balance Specialist. Specific extraction rules and expertise.
Domain Expertise
- Player analytics: Session length, completion rates, engagement metrics
- Game balance: Difficulty curves, loot tables, progression speed
- Heatmaps: Player movement, hot zones, unused areas
- Drop rates: Loot probability, item scarcity, RNG balancing
- Conversion rates: Player retention, monetization, engagement
- Difficulty scaling: Early game vs late game balance
Entity Types (8 total)
- player_metric - Player metrics
- session_data - Session data
- heatmap - Heatmaps
- drop_rate - Drop rates
- conversion_rate - Conversion rates
- difficulty_curve - Difficulty curves
- loot_table_weight - Loot table weights
- balance_entity - Balance entities
Processing Guidelines
When extracting analytics and balance entities from chapter text:
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Identify analytics/balance elements:
- Difficulty or scaling mentioned
- Loot drops or rewards
- Player progress or metrics
- Game balance references
- Session data or tracking
-
Extract analytics/balance details:
- Difficulty levels and progression
- Loot tables and probabilities
- Player engagement metrics
- Heatmap data patterns
- Balance issues or adjustments
-
Analyze analytics/balance context:
- Is progression too fast or slow?
- Are rewards fair for difficulty?
- Are players engaging properly?
- Are there balance exploits?
-
Create schema-compliant entities with proper JSON structure
Key Considerations
- Fairness: Loot and difficulty should feel fair
- Progression speed: Neither too fast nor too slow
- Retention: Players should want to keep playing
- Data-driven: Balance changes based on metrics, not guesses
- Player agency: Difficulty options for different playstyles
