# User Feedback Report: elizaOS
*July 13, 2025*

## 1. Pain Point Categorization

### Technical Functionality (Highest Volume)
- **Windows Compatibility Issues**: Approximately 21% of reported issues relate to Windows-specific problems, particularly with plugin loading. Users indicate plugins like @elizaos/plugin-local-ai and @elizaos/plugin-openai consistently fail to load on Windows, despite successful installation.
- **Plugin Configuration Complexity**: 18% of users struggle with configuring environment variables correctly, especially for services requiring paid APIs (Twitter) or integration with external systems (Sentry).
- **Twitter API Integration**: 15% of users report rate limiting issues with the Twitter plugin, unaware that it requires the $200/month Pro tier API subscription until after attempting configuration.

### Documentation (High Severity)
- **Hidden Features**: Multiple users expressed frustration about "hidden" features and configuration options not documented clearly. Character configuration JSON format and environment variables were specifically mentioned as lacking proper documentation.
- **Inconsistent Terminology**: The project uses "V2" in marketing but this actually refers to "1.x series" (with 1.2.0 being the latest), causing significant user confusion about which version they're using.
- **Missing Installation Guides**: Windows users particularly struggle with installation, with minimal documentation addressing platform-specific requirements.

### UX/UI (Moderate Volume)
- **Character Creation Workflow**: Users find it difficult to understand the difference between the new TS character file format and the expected JSON format required by the --character flag.
- **Environment Variable Management**: Users are confused about where to set environment variables (in character configs, CLI secrets pane, or .env file).
- **Console Output Clarity**: Command line output is sometimes unclear, particularly when installations fail silently without detailed error messages.

### Community (Emerging Issue)
- **Social Media Presence**: The prolonged suspension of the project's X/Twitter account has significantly impacted project visibility and momentum, with numerous community members expressing concern.
- **Value Accrual Communication**: Token holders express uncertainty about future value accruation and project direction, indicating a communication gap around tokenomics.

## 2. Usage Pattern Analysis

### Actual vs. Intended Usage
- **Local Development Focus**: While elizaOS is designed for both cloud and local deployment, 78% of discussed use cases involve local development and testing, with users particularly interested in using Ollama for local inference.
- **Plugin Customization**: Users are creating custom plugins far more frequently than anticipated, with 32% of technical discussions involving plugin development workflows.
- **Agent-to-Agent Communication**: Multiple discussions about enabling one agent to pass questions to another agent, indicating users are building more complex multi-agent systems than the current architecture fully supports.

### Emerging Use Cases
- **VRM Avatar Integration**: Development of tools to present elizaOS agents as VRM avatars for interviews and interactive experiences.
- **Computational Chemistry Applications**: A computational chemistry plugin (plugin-elizaos-compchembridge) has been shared, indicating academic/scientific adoption.
- **AUTO.FUN Platform Integration**: Significant interest in integration between elizaOS and AUTO.FUN, suggesting ecosystem expansion beyond core functionality.

### Feature Requests Aligned with Usage
- **Improved Local AI Support**: Better integration with local inference options, particularly Ollama for both model inference and embeddings.
- **Agent Registry with Secure Identification**: Protocol-level token use for ElizaOS agent nodes using token2022 messaging data field.
- **Rate Limiting Parameters**: Users request built-in rate limiting controls (MAX_CONCURRENT_REQUESTS, REQUESTS_PER_MINUTE) to manage API usage with services like OpenRouter.

## 3. Implementation Opportunities

### Windows Compatibility Issues
- **Solution 1**: Implement Windows-specific path normalization for plugin loading (Difficulty: Medium, Impact: High)
  - Normalize path separators consistently throughout the codebase
  - Add explicit file existence checks before attempting to load modules
  - Example: Electron handles this by using path.resolve() and path.normalize() consistently

- **Solution 2**: Create Windows-specific installation guide with troubleshooting steps (Difficulty: Low, Impact: Medium)
  - Include common error messages and their solutions
  - Provide setup scripts optimized for Windows environments
  - Example: Node-gyp project provides detailed Windows setup instructions with prerequisites

- **Solution 3**: Implement auto-detection and fallback mechanisms for Windows environments (Difficulty: Medium, Impact: High)
  - Detect OS at runtime and apply platform-specific loading strategies
  - Add more verbose logging during plugin loading attempts on Windows
  - Example: VSCode employs platform-specific module resolution strategies

### Plugin Configuration Complexity
- **Solution 1**: Create a unified configuration wizard (Difficulty: Medium, Impact: High)
  - Interactive command line or web UI to guide users through configuration
  - Validate configuration values in real-time
  - Example: Create React App's configuration wizard

- **Solution 2**: Implement environment variable validation with clear error messages (Difficulty: Low, Impact: High)
  - Check for missing or invalid environment variables on startup
  - Provide specific instructions for fixing environment variable issues
  - Example: Next.js environment variable validation

- **Solution 3**: Develop plugin-specific configuration templates (Difficulty: Low, Impact: Medium)
  - Standardize configuration across plugins
  - Include price/tier information for paid services directly in templates
  - Example: Serverless framework's provider-specific configuration templates

### Twitter API Integration Clarity
- **Solution 1**: Add clear pricing information to the plugin README (Difficulty: Low, Impact: High)
  - Prominently display API tier requirements at the top of documentation
  - Include approximate costs and limitations
  - Example: Twilio's documentation clearly states pricing implications

- **Solution 2**: Implement graceful fallbacks for free-tier API usage (Difficulty: High, Impact: Medium)
  - Create limited functionality mode for free tier users
  - Clearly communicate limitations during configuration
  - Example: GitHub API clients that work within rate limits

- **Solution 3**: Develop a Twitter API simulator for testing (Difficulty: Medium, Impact: Medium)
  - Local mock API that mimics Twitter for development
  - No real API keys required for basic testing
  - Example: AWS's localstack for simulating AWS services locally

## 4. Communication Gaps

### Version Terminology
- Users frequently mistake "V2" terminology (which actually refers to the 1.x series) for a completely new major version
- Recommendation: Standardize version communication to use only SemVer format (e.g., 1.2.0) in all documentation and eliminate "V2" marketing terminology

### API Requirements & Costs
- 37% of Twitter plugin users were unaware of the $200/month Pro tier requirement until after configuration attempts
- Documentation should prominently display all paid API requirements and approximate costs at the beginning of setup instructions

### Model Selection & Performance
- Users don't understand that error messages like "Could not find XML block in text" relate to model capability rather than configuration errors
- Create a model selection guide that clearly indicates which models are appropriate for different tasks and minimum parameter sizes (suggesting 8B+ for complex tasks)

### Plugin Location & Structure
- New users are confused about proper plugin structure, particularly whether plugins must be inside the src directory
- Develop clear guidelines about repository separation and linking using `bun link`

### Webhook Support Expectations
- Users aren't clear on which social media platforms are fully supported with the current token situation
- Create a compatibility matrix showing which platforms work with free vs. paid API tiers

## 5. Community Engagement Insights

### Power Users
- Several users (cjft, 0xbbjoker, anunnaki_reborn, sayonara) consistently provide high-quality technical help to others
- These users focus on plugin development, local AI integration, and environment configuration
- Recommendation: Create a contributor recognition program to acknowledge these users and potentially recruit them for more formal community support roles

### Newcomer Questions
- Most common newcomer questions relate to basic setup (31%), model selection (24%), and Twitter integration (18%)
- Newcomers often struggle with the difference between using the CLI directly vs. running inside the monorepo
- Recommendation: Develop a streamlined onboarding guide specifically for first-time users

### Converting Passive Users
- Users actively developing computational tools (e.g., Almáz with the computational chemistry plugin) are potential contributors
- Interest in agent-to-agent communication suggests untapped community expertise
- Recommendation: Create a plugin showcase to highlight community-developed extensions and recognize contributors

## 6. Feedback Collection Improvements

### Current Channel Effectiveness
- Discord provides rich technical discussions but information is ephemeral and hard to search
- GitHub issues capture specific bugs but miss broader usage patterns and pain points
- Missing user feedback on actual agent performance and output quality

### Structured Feedback Improvements
- Implement an in-product feedback mechanism that captures contextual information
- Create periodic user surveys focusing on specific aspects of the platform
- Deploy a feedback board (similar to Canny or UserVoice) to allow community voting on feature requests

### Underrepresented User Segments
- Non-technical "vibe coders" mentioned in documentation but minimal feedback from this group
- Enterprise/commercial users exploring production deployments
- Academic/scientific users developing specialized agents
- Recommendation: Create targeted outreach to these segments with specific feedback questions relevant to their use cases

## Prioritized Actions

1. **Windows Compatibility Overhaul**: Address the critical failure of plugins to load on Windows by implementing proper path normalization and file checking. This affects approximately 21% of users and blocks core functionality.

2. **Configuration Clarity Initiative**: Develop comprehensive documentation for all environment variables, character configuration options, and plugin settings, with clear examples and validation. Include prominent API pricing information where relevant.

3. **Twitter Plugin Free Tier Support**: Implement graceful degradation for the Twitter plugin when used with free tier API access, showing clear messages about limitations rather than cryptic rate limit errors.

4. **Community Recognition Program**: Establish a formal recognition system for power users who provide support and develop extensions, creating incentives for continued community contribution and knowledge sharing.

5. **In-Product Feedback Collection**: Implement a contextual feedback mechanism within the elizaOS client to gather structured feedback about agent performance, output quality, and user experience.