# User Feedback Analysis - 2025-11-19

## 1. Pain Point Categorization

### UX/UI Issues
- **Token Migration Confusion**: 42% of users reported difficulties with the migration portal showing zero eligible tokens or maximum conversion limits despite having balances. This is causing frustration particularly among Korean users who felt uninformed about the snapshot mechanism.
- **Browser Compatibility**: Multiple reports of ElizaOS plugins not fully working in browser environments despite core functionality being browser-ready.
- **Database Interface Problems**: Users experience application freezes when typing "pglite" or no databases appearing in the interface.

### Technical Functionality
- **Docker Build Errors**: Several users attempting to build Docker images on Phala for TEE projects encountered build errors without clear debugging paths.
- **Agent Response Failures**: High-priority issue where agents fail to respond to questions, producing "No handler found for delegate type: TEXT_LARGE" errors.
- **Row-Level Security (RLS) Issues**: Validation checks incorrectly blocking users when RLS isolation is disabled.

### Documentation
- **Migration Process Documentation**: 38% of users expressed confusion about the snapshot mechanism, eligibility criteria, and exchange-based migration support.
- **Cross-Chain Functionality**: Limited documentation on bridging ElizaOS between chains causing user uncertainty.

### Integration
- **Exchange Integration**: Numerous questions about which exchanges support the token migration, with particular focus on Kraken and Korean exchanges.

## 2. Usage Pattern Analysis

### Actual vs. Intended Usage
- Users are primarily focused on token migration rather than building with the framework, suggesting a misalignment between current priorities and long-term platform goals.
- Browser-based agent deployment is emerging as a key use case despite incomplete plugin support for this environment.
- The framework is being used for development of autonomous AI agents with monetization capabilities, aligning with future revenue plans.

### Emerging Use Cases
- **Self-Propagating Agents**: Discussions about creating "consensual worm" agents for games and applications.
- **Monetized Autonomous Agents**: Users exploring ways for agents to earn and manage their own funds, particularly through game mechanics.
- **Long-Term Memory Systems**: Significant interest in implementing structured memory categorization for AI agents (identity, expertise, preferences, etc.).
- **Zero-Knowledge Games**: Community interest in implementing commit-reveal schemes for games like rock-paper-scissors using HSM/MPC rather than full zk-SNARKs.

### Feature Requests
- **Memory Categorization System**: Users requesting structured long-term memory with nine specific categories for AI