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research/taskmaster-ai.md
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research/taskmaster-ai.md
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# Claude Task Master Research & Integration Plan
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## Project Overview
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**Claude Task Master** (https://github.com/eyaltoledano/claude-task-master) is an AI-powered task management system that leverages Claude's capabilities for intelligent task breakdown, prioritization, and execution tracking.
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### Key Features Analysis
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#### Core Capabilities
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- **Intelligent Task Breakdown**: Automatically decomposes complex projects into manageable subtasks
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- **Context-Aware Planning**: Uses AI to understand project requirements and dependencies
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- **Progress Tracking**: Monitors task completion and adjusts plans dynamically
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- **Natural Language Interface**: Allows task management through conversational commands
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- **Integration Ready**: Designed to work with existing development workflows
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#### Technical Architecture
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- **Backend**: Node.js/Python-based task orchestration
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- **AI Integration**: Claude API for task analysis and planning
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- **Storage**: JSON/Database for task persistence
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- **API**: RESTful endpoints for external integrations
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## Workflow Compatibility Assessment
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### Current Home-lab Methodology Alignment
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#### ✅ Strong Fits
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1. **Infrastructure-as-Code Philosophy**
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- Task Master's structured approach aligns with your NixOS configuration management
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- Can track infrastructure changes as tasks with dependencies
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2. **Service-Oriented Architecture**
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- Fits well with your microservices approach (Transmission, monitoring, etc.)
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- Can manage service deployment and configuration tasks
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3. **Documentation-Driven Development**
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- Integrates with your markdown-based documentation workflow
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- Can auto-generate task documentation and progress reports
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#### ⚠️ Considerations
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1. **Resource Overhead**
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- Additional service to manage in your infrastructure
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- API rate limits for Claude integration
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2. **Data Privacy**
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- Task data would be processed by Claude API
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- Need to ensure sensitive infrastructure details are handled appropriately
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## Integration Strategy
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### Phase 1: Core Installation & Setup
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#### Prerequisites
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```bash
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# Dependencies for Home-lab integration
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- Node.js runtime environment
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- Claude API access (Anthropic)
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- Docker/Podman for containerization
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- NixOS service configuration
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```
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#### Installation Plan
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1. **Clone and Setup**
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```bash
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cd /home/geir/Home-lab/services
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git clone https://github.com/eyaltoledano/claude-task-master.git taskmaster
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cd taskmaster
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```
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2. **NixOS Service Configuration**
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- Create `taskmaster.nix` service definition
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- Configure API keys and environment variables
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- Set up reverse proxy through existing nginx setup
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3. **Environment Configuration**
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```env
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CLAUDE_API_KEY=<your-key>
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TASKMASTER_PORT=3001
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DATABASE_URL=sqlite:///mnt/storage/taskmaster.db
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```
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### Phase 2: GitHub Copilot Integration
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#### Integration Points
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1. **Code Task Generation**
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- Use Copilot to generate coding tasks from repository analysis
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- Automatic task creation from GitHub issues and PRs
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2. **Development Workflow Enhancement**
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```typescript
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// Example integration hook
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interface CopilotTaskBridge {
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generateTasksFromCode(filePath: string): Task[];
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updateTaskProgress(taskId: string, codeChanges: CodeDiff[]): void;
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suggestNextSteps(currentTask: Task): Suggestion[];
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}
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```
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3. **VS Code Extension Development**
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- Custom extension to bridge Copilot suggestions with Task Master
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- Real-time task updates based on code changes
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### Phase 3: Context7 MCP Integration
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#### Model Context Protocol Benefits
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1. **Unified Context Management**
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- Task Master tasks as context for Claude conversations
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- Project state awareness across all AI interactions
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2. **Cross-Service Communication**
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```json
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{
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"mcp_config": {
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"services": {
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"taskmaster": {
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"endpoint": "http://sleeper-service:3001/api",
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"capabilities": ["task_management", "progress_tracking"]
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},
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"github_copilot": {
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"integration": "vscode_extension",
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"context_sharing": true
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}
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}
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}
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}
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```
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3. **Context Flow Architecture**
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```
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GitHub Copilot → Context7 MCP → Task Master → Claude API
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↑ ↓
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VS Code Editor ←─────── Task Updates ←─────── AI Insights
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```
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## Implementation Roadmap
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### Week 1: Foundation
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- [ ] Set up Task Master on sleeper-service
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- [ ] Configure basic NixOS service
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- [ ] Test Claude API integration
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- [ ] Create initial task templates for Home-lab projects
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### Week 2: GitHub Integration
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- [ ] Develop Copilot bridge extension
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- [ ] Set up GitHub webhook integration
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- [ ] Create automated task generation from repository events
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- [ ] Test code-to-task mapping
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### Week 3: MCP Integration
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- [ ] Implement Context7 MCP protocol support
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- [ ] Create unified context sharing system
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- [ ] Develop cross-service communication layer
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- [ ] Test end-to-end workflow
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### Week 4: Optimization & Documentation
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- [ ] Performance tuning and monitoring
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- [ ] Complete integration documentation
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- [ ] Create user workflow guides
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- [ ] Set up backup and recovery procedures
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## NixOS Service Configuration Preview
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```nix
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# /home/geir/Home-lab/machines/sleeper-service/services/taskmaster.nix
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{ config, pkgs, ... }:
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{
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services.taskmaster = {
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enable = true;
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port = 3001;
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user = "sma";
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group = "users";
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environmentFile = "/etc/taskmaster/env";
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dataDir = "/mnt/storage/taskmaster";
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};
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# Nginx reverse proxy configuration
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services.nginx.virtualHosts."taskmaster.home-lab" = {
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locations."/" = {
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proxyPass = "http://localhost:3001";
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proxyWebsockets = true;
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};
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};
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# Firewall configuration
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networking.firewall.allowedTCPPorts = [ 3001 ];
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}
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```
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## Benefits for Home-lab Workflow
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### Immediate Improvements
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1. **Project Visibility**: Clear overview of all infrastructure tasks and their status
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2. **Dependency Management**: Automatic tracking of service dependencies and update sequences
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3. **Documentation Automation**: AI-generated task documentation and progress reports
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4. **Workflow Optimization**: Intelligent task prioritization based on system state
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### Long-term Value
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1. **Knowledge Retention**: Comprehensive history of infrastructure decisions and changes
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2. **Onboarding**: New team members can quickly understand project structure through task history
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3. **Compliance**: Automated tracking for security updates and maintenance tasks
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4. **Scalability**: Framework for managing larger infrastructure deployments
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## Risk Assessment & Mitigation
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### Technical Risks
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- **API Dependencies**: Mitigate with local fallback modes
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- **Data Loss**: Regular backups to /mnt/storage/backups
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- **Performance Impact**: Resource monitoring and limits
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### Security Considerations
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- **API Key Management**: Use NixOS secrets management
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- **Network Isolation**: Restrict external API access through firewall rules
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- **Data Encryption**: Encrypt sensitive task data at rest
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## Conclusion
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Claude Task Master shows strong alignment with your Home-lab methodology and could significantly enhance project management capabilities. The integration with GitHub Copilot and Context7 MCP would create a powerful AI-assisted development environment that maintains context across all project activities.
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**Recommendation**: Proceed with implementation, starting with Phase 1 to establish the foundation and evaluate real-world performance in your environment.
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