DomaScore Development Plan - Parallel Execution Strategy

🎯 Objective

Build DomaScore AI-powered domain valuation platform efficiently using parallel Claude Code sessions with real implementation and testing.

📋 Project Overview

Platform: AI-powered domain valuation and trend analysis
Integration: Doma Protocol (Subgraph + Poll API)
Tech Stack: Next.js frontend + Node.js backend + ML models
Testing: Playwright MCP for all features
Deployment: Real implementation only (NO MOCKING)

🚀 Execution Strategy

Parallel Development Approach

6 Parallel Tracks - Each can run in separate Claude Code sessions
Progress Tracking - Each session updates PROGRESS_REPORT.md
Integration Points - Clear handoff between tracks
Testing Requirements - Playwright tests for each feature
Fresh Session Support - Self-contained prompts with context

Session Coordination

Track 1: Data Pipeline    ←→ Track 3: ML Models
Track 2: Frontend Core    ←→ Track 4: Real-time Analytics
Track 5: API Layer       ←→ Track 6: Testing & Integration

📊 Development Tracks

Track 1: Data Pipeline & Infrastructure (6 hours)

Session Purpose: Build data collection and processing pipeline Prerequisites: Environment setup, API keys Integration Point: Provides data for ML models (Track 3)

Key Deliverables:

Doma Subgraph GraphQL client
Historical sales data fetcher
Data preprocessing pipeline
Feature extraction service
Database schema setup

Track 2: Frontend Core & UI (8 hours)

Session Purpose: Build main user interface and components Prerequisites: Frontend template understanding Integration Point: Consumes API from Track 5

Key Deliverables:

Dashboard layout and navigation
Domain valuation interface
Portfolio analysis tools
Responsive design implementation
Wallet connection integration

Track 3: ML Models & Scoring (10 hours)

Session Purpose: Develop AI valuation and rarity scoring Prerequisites: Data pipeline from Track 1 Integration Point: Provides models for API (Track 5)

Key Deliverables:

Domain valuation ML models
Rarity scoring algorithm
Feature engineering pipeline
Model training and validation
Prediction confidence intervals

Track 4: Real-time Analytics & Events (6 hours)

Session Purpose: Build live market analytics Prerequisites: Poll API integration knowledge Integration Point: Feeds data to frontend (Track 2)

Key Deliverables:

Poll API integration service
WebSocket server for real-time updates
Market analytics calculations
Event processing pipeline
Trend detection algorithms

Track 5: API Layer & Integration (4 hours)

Session Purpose: Build RESTful API and integration layer Prerequisites: ML models (Track 3) and data pipeline (Track 1) Integration Point: Serves frontend (Track 2) and external clients

Key Deliverables:

RESTful API endpoints
Authentication and rate limiting
API documentation
SDK development
Error handling and validation

Track 6: Testing & Quality Assurance (4 hours)

Session Purpose: Comprehensive testing and integration Prerequisites: All other tracks partially complete Integration Point: Validates all implementations

Key Deliverables:

Playwright end-to-end tests
Integration test suite
Performance testing
Security validation
Deployment verification

🔄 Progress Tracking System

PROGRESS_REPORT.md Structure

Each session MUST update this file at completion:

# DomaScore Development Progress

## Session Reports
### [TIMESTAMP] Track X: [Session Name]
- **Status**: [COMPLETED/IN_PROGRESS/BLOCKED]
- **Claude Session ID**: [Generated ID]
- **Deliverables Completed**:
  - ✅ [Item 1]
  - ✅ [Item 2]
  - ⚠️ [Item 3 - Issues noted]
- **Integration Points Ready**: [List ready handoffs]
- **Blockers**: [Any issues requiring attention]
- **Next Session Requirements**: [What next session needs]
- **Testing Results**: [Playwright test outcomes]
- **Files Modified/Created**: [List with line counts]

## Overall Status
- **Tracks Completed**: X/6
- **Critical Path Status**: [ON_TRACK/DELAYED/BLOCKED]
- **Integration Health**: [GOOD/ISSUES/CRITICAL]

🎯 Execution Prompts for Fresh Claude Code Sessions

Universal Session Context

CONTEXT FOR FRESH CLAUDE CODE SESSION:

You are working on DomaScore - AI-powered domain valuation platform integrating with Doma Protocol.

PROJECT STRUCTURE:
- Root: /Users/gabrielantonyxaviour/Documents/projects/doma/doma-score/
- Frontend: /frontend/ (Next.js with existing components)
- Contracts: /contracts/ (Smart contract templates)
- Docs: /doma-docs/ (Doma Protocol documentation)

CRITICAL REQUIREMENTS:
1. NO MOCKING - Everything must be real implementation
2. BUILD AND TEST - Use Playwright MCP for testing each feature
3. UPDATE PROGRESS - Must update PROGRESS_REPORT.md at session end
4. READ EXISTING - Always check current progress first

DOMA INTEGRATION:
- Subgraph: https://api-testnet.doma.xyz/graphql
- Poll API: https://api-testnet.doma.xyz/v1/poll
- Authentication: Requires API key in headers

YOUR TRACK: [TRACK_NAME]
DEPENDENCIES: [LIST_OF_DEPENDENCIES]

Track 1 Prompt: Data Pipeline

[UNIVERSAL_CONTEXT]

YOUR MISSION: Build data collection and processing pipeline for DomaScore

SPECIFIC TASKS:
1. Create DomaSubgraphClient service
   - Connect to https://api-testnet.doma.xyz/graphql
   - Implement queries for TokenPurchasedActivity events
   - Add pagination and error handling
   - Cache responses with 5-minute TTL

2. Build data preprocessing pipeline
   - Extract domain features (length, patterns, keywords)
   - Process historical sales data
   - Create ML-ready datasets
   - Store in PostgreSQL/MongoDB

3. Implement feature extraction service
   - Domain length, character patterns
   - TLD classification and scoring
   - Keyword relevance analysis
   - Phonetic quality scoring

TESTING REQUIREMENTS:
- Playwright tests for GraphQL client
- Data validation tests
- Feature extraction accuracy tests
- Performance benchmarks

COMPLETION CRITERIA:
- ✅ GraphQL client fetching real data
- ✅ Feature extraction working for 100+ domains
- ✅ Database schema created and populated
- ✅ All tests passing
- ✅ PROGRESS_REPORT.md updated

HANDOFF TO TRACK 3:
- Provide sample dataset with features
- Document data schema and access patterns
- Export model training interface

Track 2 Prompt: Frontend Core

[UNIVERSAL_CONTEXT]

YOUR MISSION: Build main user interface and dashboard components

SPECIFIC TASKS:
1. Set up dashboard layout using existing template
   - Navigation with wallet connection
   - Responsive grid for analytics widgets
   - Real-time data providers setup
   - Theme and styling consistency

2. Create domain valuation interface
   - Search input with autocomplete
   - Instant valuation display
   - Score breakdown visualizations
   - Comparable sales table
   - Export functionality

3. Build portfolio analysis tools
   - Bulk domain CSV upload
   - Portfolio summary statistics
   - Individual domain cards
   - Risk assessment display

4. Implement real-time components
   - WebSocket connections for live updates
   - Chart.js/Recharts integration
   - Loading states and error handling
   - Offline state management

TESTING REQUIREMENTS:
- Playwright E2E tests for all user flows
- Component unit tests
- Accessibility testing
- Mobile responsiveness tests
- Performance metrics

COMPLETION CRITERIA:
- ✅ Complete dashboard with navigation
- ✅ Working valuation interface
- ✅ Portfolio analysis functional
- ✅ Real-time updates working
- ✅ All Playwright tests passing
- ✅ PROGRESS_REPORT.md updated

INTEGRATION POINTS:
- Consumes API endpoints from Track 5
- Displays ML predictions from Track 3
- Shows real-time data from Track 4

Track 3 Prompt: ML Models & Scoring

[UNIVERSAL_CONTEXT]

YOUR MISSION: Develop AI valuation models and rarity scoring algorithms

SPECIFIC TASKS:
1. Build domain valuation ML models
   - Random Forest baseline model
   - Neural network for complex patterns
   - Feature engineering pipeline
   - Cross-validation with temporal splits
   - Confidence interval predictions

2. Create rarity scoring algorithm
   - Character pattern analysis
   - Keyword relevance scoring
   - TLD premium classification
   - Composite score calculation (0-100)
   - Detailed breakdown reporting

3. Implement model training pipeline
   - Automated retraining system
   - Model versioning and persistence
   - Performance tracking and validation
   - A/B testing framework

4. Create prediction service
   - Real-time inference API
   - Batch processing capability
   - Model serving infrastructure
   - Caching and optimization

TESTING REQUIREMENTS:
- Model accuracy tests (>70% target)
- Prediction stability tests
- Performance benchmarks
- Edge case validation
- Playwright integration tests

COMPLETION CRITERIA:
- ✅ Working ML models with >70% accuracy
- ✅ Rarity scoring algorithm functional
- ✅ Training pipeline operational
- ✅ Prediction service ready
- ✅ All tests passing
- ✅ PROGRESS_REPORT.md updated

DEPENDENCIES:
- Requires data from Track 1
- Provides models to Track 5

Track 4 Prompt: Real-time Analytics

[UNIVERSAL_CONTEXT]

YOUR MISSION: Build real-time market analytics and event processing

SPECIFIC TASKS:
1. Integrate Doma Poll API
   - Set up polling mechanism with acknowledgment
   - Filter relevant event types
   - Handle reconnection and error recovery
   - Store events for analysis

2. Build WebSocket server
   - Real-time event broadcasting
   - Client subscription management
   - Event transformation and enrichment
   - Rate limiting and scaling

3. Create market analytics engine
   - Trading volume calculations
   - Price movement tracking
   - Market sentiment indicators
   - Trend momentum analysis

4. Implement trend detection
   - Keyword trend analysis
   - TLD performance tracking
   - Anomaly detection system
   - Predictive trend forecasting

TESTING REQUIREMENTS:
- Playwright tests for real-time updates
- WebSocket connection tests
- Event processing validation
- Analytics accuracy tests
- Load testing for scalability

COMPLETION CRITERIA:
- ✅ Poll API integration working
- ✅ WebSocket server operational
- ✅ Market analytics functional
- ✅ Trend detection active
- ✅ All tests passing
- ✅ PROGRESS_REPORT.md updated

INTEGRATION POINTS:
- Feeds data to Track 2 frontend
- Provides trends to Track 5 API

Track 5 Prompt: API Layer

[UNIVERSAL_CONTEXT]

YOUR MISSION: Build RESTful API and integration layer

SPECIFIC TASKS:
1. Create Express.js API server
   - RESTful endpoint structure
   - Authentication with API keys
   - Rate limiting middleware
   - Request validation
   - Error handling

2. Implement core endpoints
   - POST /api/v1/valuations (single domain)
   - POST /api/v1/valuations/batch (bulk)
   - GET /api/v1/scores/:domain
   - GET /api/v1/trends
   - GET /api/v1/analytics/market

3. Build integration layer
   - ML model service integration
   - Data pipeline connections
   - Real-time analytics access
   - Caching layer implementation

4. Create API documentation
   - OpenAPI/Swagger specification
   - SDK generation
   - Code examples
   - Integration guides

TESTING REQUIREMENTS:
- Playwright API endpoint tests
- Authentication testing
- Rate limiting validation
- Performance benchmarks
- Error handling verification

COMPLETION CRITERIA:
- ✅ RESTful API fully functional
- ✅ All endpoints tested and documented
- ✅ Integration layer working
- ✅ Performance requirements met
- ✅ All tests passing
- ✅ PROGRESS_REPORT.md updated

DEPENDENCIES:
- Requires ML models from Track 3
- Requires data pipeline from Track 1
- Serves frontend from Track 2

Track 6 Prompt: Testing & QA

[UNIVERSAL_CONTEXT]

YOUR MISSION: Comprehensive testing and quality assurance

SPECIFIC TASKS:
1. Create comprehensive test suite
   - E2E Playwright tests for all user flows
   - Integration tests for all APIs
   - Performance tests for all components
   - Security validation tests

2. Validate complete system integration
   - Data flow from Doma → ML → API → Frontend
   - Real-time updates working end-to-end
   - Error handling across all layers
   - Scalability under load

3. Perform quality assurance
   - Code quality and standards
   - Security best practices
   - Performance optimization
   - User experience validation

4. Prepare deployment verification
   - Environment configuration tests
   - Deployment pipeline validation
   - Monitoring and alerting setup
   - Documentation completeness

TESTING REQUIREMENTS:
- Complete Playwright test coverage
- Load testing with realistic scenarios
- Security penetration testing
- Cross-browser compatibility
- Mobile device testing

COMPLETION CRITERIA:
- ✅ All systems integrated and tested
- ✅ Performance benchmarks met
- ✅ Security validation complete
- ✅ Deployment ready
- ✅ All tests passing
- ✅ PROGRESS_REPORT.md updated

DEPENDENCIES:
- Requires all other tracks to be functional

🔧 Environment Setup Requirements

Pre-Session Checklist

# 1. Verify environment variables
- DOMA_API_KEY=your_doma_api_key
- DATABASE_URL=postgresql://user:pass@localhost:5432/domascope
- REDIS_URL=redis://localhost:6379

# 2. Install dependencies
cd frontend && npm install
cd ../backend && npm install

# 3. Database setup
npm run db:setup
npm run db:migrate

# 4. Verify Doma connections
curl -H "Api-Key: $DOMA_API_KEY" https://api-testnet.doma.xyz/v1/poll

Integration Verification

# Test GraphQL connection
curl -X POST https://api-testnet.doma.xyz/graphql \
  -H "Content-Type: application/json" \
  -d '{"query":"{ names(take: 1) { items { name } } }"}'

# Test Poll API
curl -H "Api-Key: $DOMA_API_KEY" https://api-testnet.doma.xyz/v1/poll?limit=1

📈 Success Metrics

Technical KPIs

Business KPIs

Accurate valuations for 90% of test domains
3+ emerging trends identified
1000+ domains in portfolio analysis
Complete developer API documentation
Working demo with real data

⚠️ Critical Considerations

No Mocking Policy

All data must come from real Doma APIs
ML models must train on actual historical data
Frontend must display real valuations
Testing must use actual domain examples

Integration Dependencies

Track 1 (Data) → Track 3 (ML) → Track 5 (API) → Track 2 (Frontend)
Track 4 (Real-time) → Track 2 (Frontend)
Track 6 (Testing) ← All Tracks

Risk Mitigation

API Rate Limits: Implement caching and request optimization
Data Quality: Validate and clean all data inputs
Model Performance: Start simple, add complexity incrementally
Integration Issues: Test handoffs between tracks early
Time Constraints: Focus on MVP first, enhance later

🎯 Execution Command

To start a track in a fresh Claude Code session:

Copy the appropriate track prompt above, replace [UNIVERSAL_CONTEXT] with the universal session context, and execute in Claude Code.

CRITICAL: Always read PROGRESS_REPORT.md first to understand current status before starting!

This plan ensures efficient parallel development while maintaining quality and real implementation standards.

FilesExpand file tree

DEVELOPMENT_PLAN.md

Latest commit

History

DEVELOPMENT_PLAN.md

File metadata and controls

DomaScore Development Plan - Parallel Execution Strategy

🎯 Objective

📋 Project Overview

🚀 Execution Strategy

Parallel Development Approach

Session Coordination

📊 Development Tracks

Track 1: Data Pipeline & Infrastructure (6 hours)

Track 2: Frontend Core & UI (8 hours)

Track 3: ML Models & Scoring (10 hours)

Track 4: Real-time Analytics & Events (6 hours)

Track 5: API Layer & Integration (4 hours)

Track 6: Testing & Quality Assurance (4 hours)

🔄 Progress Tracking System

PROGRESS_REPORT.md Structure

🎯 Execution Prompts for Fresh Claude Code Sessions

Universal Session Context

Track 1 Prompt: Data Pipeline

Track 2 Prompt: Frontend Core

Track 3 Prompt: ML Models & Scoring

Track 4 Prompt: Real-time Analytics

Track 5 Prompt: API Layer

Track 6 Prompt: Testing & QA

🔧 Environment Setup Requirements

Pre-Session Checklist

Integration Verification

📈 Success Metrics

Technical KPIs

Business KPIs

⚠️ Critical Considerations

No Mocking Policy

Integration Dependencies

Risk Mitigation

🎯 Execution Command