# Farclore: Path to Farhalla Product Specification

## Overview
Farclore is a Farcaster Frame app that analyzes a user's social graph to generate "builder profiles" showing their contributions, skills, and community recognition. The product has two phases: an MVP with basic querying capabilities and a 1.0 release with token-gated access.

## Product Phases

### MVP
A single-page Frame allowing users to query Farcaster handles and generate profiles based on mentions in other users' casts.

### Version 1.0
Same functionality as MVP but requiring $LORE tokens to generate profiles, with in-Frame purchase capabilities via Farcaster wallet.

## Technical Specifications

### MVP Components

1. **Frame Interface**
- Single input field for Farcaster handle
- "Generate Profile" button
- Results display showing extracted information

2. **Backend Processing**
- Neynar API integration to fetch mentions of queried handle
- LLM processing of mentions to extract:
* Skills and attributes
* Projects contributed to
* Praise received (and from whom)
* Community recognition patterns

3. **Data Storage**
- Cache of generated profiles
- Simple relationship database
- Query history tracking

### Version 1.0 Additional Components

1. **Token Integration**
- $LORE token smart contract
- Farcaster wallet integration
- Token-gated profile generation

2. **Enhanced Features**
- More detailed relationship mapping
- Expanded historical data analysis
- Profile sharing capabilities

## User Flow - MVP

1. User sees Frame with "Who would you like to learn about?" prompt
2. User enters a Farcaster handle (e.g., @dwr)
3. System fetches mentions of that handle from Farcaster API
4. LLM analyzes mentions to extract relationships and praise
5. System generates and displays a profile showing:
- Top skills (based on mentions)
- Projects worked on
- Notable praise received
- Community connections

## Technical Implementation

### Frame Development
- Next.js Frame app hosted on Vercel
- Tailwind CSS for styling
- App Router for Frame navigation

### Backend Services
- Node.js/Express API or serverless functions
- Neynar Hub API for Farcaster data
- OpenAI API for content analysis
- Supabase for data storage

### API Integrations
- Neynar API for Farcaster data
- OpenAI API for LLM processing
- Onchain data for Version 1.0

## Development Milestones

### MVP (4-6 Weeks)
1. **Week 1-2**: Frame setup and API integration
2. **Week 3-4**: LLM processing implementation
3. **Week 5-6**: Testing and refinement

### Version 1.0 (Additional 4-6 Weeks)
1. **Week 1-2**: $LORE token development
2. **Week 3-4**: Farcaster wallet integration
3. **Week 5-6**: Testing and security review

## Technical Considerations

1. **Performance**
- Implement caching for frequently queried profiles
- Consider rate limits for Neynar and OpenAI APIs
- Optimize LLM prompt for extraction efficiency

2. **Data Freshness**
- Implement background refreshing of popular profiles
- Clear cache for profiles older than 24 hours

3. **Error Handling**
- Handle API rate limits gracefully
- Provide meaningful feedback for failed queries
- Implement fallbacks when extraction fails

## Future Potential Enhancements
- Network visualization showing relationship graphs
- Time-based analysis showing influence growth
- Project-based queries to see contributors
- Comparative analysis between builders

This specification provides a complete roadmap for a developer to implement both the MVP and Version 1.0 of Farclore, with clear technical requirements and implementation guidance.