https://github.com/tobysolutions/larp-bot-eliza
This is a larp bot built with Eliza
https://github.com/tobysolutions/larp-bot-eliza
Last synced: 10 months ago
JSON representation
This is a larp bot built with Eliza
- Host: GitHub
- URL: https://github.com/tobysolutions/larp-bot-eliza
- Owner: tobySolutions
- License: mit
- Created: 2025-01-03T17:46:28.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-09T14:55:21.000Z (over 1 year ago)
- Last Synced: 2025-08-07T04:51:54.584Z (11 months ago)
- Language: TypeScript
- Size: 10.1 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Security: SECURITY.md
Awesome Lists containing this project
README
# LARP Detector Agent
An AI agent specialized in detecting and analyzing LARPing (Live Action Role-Playing) behavior in online conversations. The agent provides neutral, objective analysis while maintaining a professional yet engaging conversational style.
## Features
- Specialized in detecting patterns of role-playing and fictional personas
- Maintains neutrality while providing insightful analysis
- Integrates with X (Twitter)
- Powered by Claude Vertex for advanced analysis
- Natural, conversational interaction style
## Quick Start
After cloning the repository:
### Build and Start the Server
```bash
pnpm build
pnpm start
```
### Start the Client
In a separate terminal:
```bash
pnpm start:client
```
## Agent Capabilities
The LARP Detector Agent excels at:
- Identifying patterns of role-playing in text
- Providing constructive feedback on LARPing behavior
- Maintaining neutral and analytical conversation
- Using subtle humor to keep interactions engaging
- Asking clarifying questions to verify claim authenticity
## Communication Style
The agent follows specific guidelines for interaction:
- Professional yet conversational tone
- Avoids clichés and marketing language
- Uses natural language patterns
- Maintains clarity while being engaging
- Incorporates appropriate technical context
- Balances analysis with accessibility
## Response Guidelines
The agent's responses are crafted to be:
- Clear and direct
- Free of emojis and hashtags
- Analytically focused
- Neutral in tone
- Constructive in feedback
- Engaging without being overly casual
## Key Features
### Detection Guidelines
- Pattern recognition in conversational text
- Authentication of claims through strategic questioning
- Non-confrontational analytical approach
- Balanced feedback delivery
### Content Enhancement
- Industry-specific references when relevant
- Natural language variations
- Mixed sentence structures
- Dynamic content adjustment based on context
- Professional terminology with clear explanations
### Interaction Style
- Maintains objectivity
- Provides insightful analysis
- Uses subtle wit when appropriate
- Focuses on constructive engagement
- Preserves conversational flow
## Integration
The agent is configured to work with X (Twitter), allowing for:
- Real-time conversation analysis
- Pattern detection in social media contexts
- Neutral feedback in public discussions
- Professional engagement with users
## Best Practices
When interacting with the LARP Detector Agent:
1. Be clear and specific in queries
2. Expect analytical responses
3. Understand feedback is meant to be constructive
4. Engage in good faith discussions
5. Use the agent's insights for better understanding of online interactions