193 lines
9.2 KiB
Markdown
193 lines
9.2 KiB
Markdown
# Directus Task Management Suite
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## Project Overview
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A comprehensive task management system built on Directus CMS that integrates seamlessly with the existing AI-powered development ecosystem. This project provides intelligent task orchestration, automated workflow management, and deep integration with Claude Code agents, BMad methodology, and the established Task Master system.
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**Status**: Phase 1 - Planning Complete ✅
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**Next Phase**: Core Implementation
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**Target**: Production-ready task management with AI integration
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## Quick Start
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### For Developers
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```bash
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# 1. Review planning documents
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cd projects/directus-task-management/planning/
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ls -la # See all BMad planning outputs
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# 2. Initialize Task Master project for this work
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task-master init
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task-master parse-prd .taskmaster/docs/prd.txt
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# 3. Set up development environment
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# (Follow implementation guides in 06-implementation-guides.md)
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```
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### For Project Managers
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- **Vision**: [01-bmad-prd.md](planning/01-bmad-prd.md) - Complete product requirements
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- **Sprint Planning**: [05-bmad-user-stories.md](planning/05-bmad-user-stories.md) - 4 sprints, 13 user stories
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- **Timeline**: 8 weeks total, 4 phases, incremental delivery
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### For System Architects
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- **Architecture**: [02-bmad-architecture.md](planning/02-bmad-architecture.md) - 10 collections, 22 MCP tools
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- **Integration**: Seamless with existing Directus, Task Master, Claude Code, BMad systems
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- **Performance**: Designed for 10,000+ tasks, 100+ projects, 99.9% uptime
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## Planning Documents Navigation
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### 📋 Phase 1: Strategic Planning (Complete)
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| Document | Purpose | Key Deliverables |
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|----------|---------|-----------------|
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| **[01-bmad-prd.md](planning/01-bmad-prd.md)** | Product Requirements | Vision, features, success metrics, 4-phase roadmap |
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| **[02-bmad-architecture.md](planning/02-bmad-architecture.md)** | Technical Architecture | 10 collections, 22 MCP tools, integration patterns |
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| **[03-bmad-research-analysis.md](planning/03-bmad-research-analysis.md)** | Market & Technical Research | Industry analysis, Directus patterns, AI integration |
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| **[04-bmad-validation.md](planning/04-bmad-validation.md)** | Feasibility Validation | Technical validation, risk assessment, GO decision |
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| **[05-bmad-user-stories.md](planning/05-bmad-user-stories.md)** | Sprint Planning | 13 user stories, 4 sprints, velocity estimation |
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| **[06-implementation-guides.md](planning/06-implementation-guides.md)** | Development Guides | Code examples, setup instructions, best practices |
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## Key Architecture Decisions
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### ✅ Validated Technical Decisions
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- **Platform**: Directus CMS (existing infrastructure at https://enias.zeabur.app)
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- **Integration**: MCP server extension (22 new tools + 40 existing)
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- **Sync Strategy**: Bidirectional with Task Master (conflict resolution)
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- **AI Integration**: Native Claude Code agent context provision
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- **Database**: 10 new collections with strategic indexing
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- **Performance**: <100ms response, cursor-based pagination, Redis caching
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### 🎯 Success Metrics
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- **Efficiency**: 70% time savings in task management workflows
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- **AI Integration**: 80% of tasks created through AI assistance
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- **Adoption**: 100+ tasks created in first month
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- **Reliability**: 99.9% uptime, <1% data integrity issues
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- **Team Collaboration**: Web UI enabling multi-user workflows
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## Implementation Roadmap
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### Phase 2: Core Implementation (Next - Weeks 1-4)
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**Sprint 1-2: Foundation & AI Integration**
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- [ ] Implement 10 Directus collections with relationships
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- [ ] Build 22 MCP tools for task operations
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- [ ] Create AI-powered task creation system
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- [ ] Set up Claude Code agent context integration
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**Deliverables:**
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- Functional task management via Directus admin interface
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- Natural language task creation
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- Agent context provision through MCP tools
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- Basic reporting dashboard
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### Phase 3: Workflow Integration (Weeks 5-8)
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**Sprint 3-4: BMad & Task Master Integration**
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- [ ] BMad workflow templates and tracking
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- [ ] Task Master bidirectional synchronization
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- [ ] Team collaboration features
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- [ ] Advanced analytics dashboard
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**Deliverables:**
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- BMad methodology fully supported
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- Seamless Task Master integration
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- Team collaboration through web interface
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- Production-ready performance optimization
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### Phase 4: Strategic Web Management (Future)
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**Long-term Vision: Unified Strategic + Tactical Interface**
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- Strategic Level: BMad project/epic management via web
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- Tactical Level: Task Master functionality via web UI
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- Unified Interface: Single pane for both strategic and tactical work
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## Integration Overview
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### Current System Integration
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```
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┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
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│ Claude Code │ │ BMad Core │ │ Task Master │
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│ Agents │ │ Methodology │ │ CLI System │
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│ (10+ agents) │ │ (Templates & │ │ (Granular │
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│ │ │ Workflows) │ │ Tracking) │
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└─────────┬───────┘ └─────────┬────────┘ └─────────┬───────┘
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│ │ │
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│ ┌───────▼────────┐ │
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│ │ │ │
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└─────────────►│ Directus │◄─────────────┘
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│ Task Management│
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│ Suite │
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│ │
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└────────────────┘
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```
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### Benefits of Integration
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1. **Single Source of Truth**: Centralized task data with web UI
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2. **AI-First Design**: Built for agent consumption and automation
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3. **Workflow Harmony**: Extends capabilities without disruption
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4. **Team Collaboration**: Web interface for multi-user access
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5. **Data Integrity**: Backup, recovery, and audit trails
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## Next Steps
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### Immediate Actions (This Week)
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1. **Task Master Setup**: Initialize Task Master project for this implementation work
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2. **Environment Preparation**: Set up development environment with Directus access
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3. **Schema Design**: Begin implementing the 10 core collections
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4. **MCP Development**: Start building the first batch of MCP tools
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### Development Approach
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1. **BMad Methodology**: Follow established BMad patterns for implementation
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2. **TDD Practice**: Write tests first, implement to pass, refactor for quality
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3. **Incremental Delivery**: Each sprint delivers working functionality
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4. **Documentation First**: Maintain comprehensive docs throughout development
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### Resource Requirements
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- **Development Time**: 8 weeks (2 developers recommended)
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- **Infrastructure**: Existing Directus instance (no additional cost)
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- **Integration Effort**: 22 new MCP tools + sync service development
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- **Testing**: Comprehensive testing with existing Task Master projects
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## Success Criteria
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### Technical Success ✅
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- All 10 collections operational with proper relationships
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- 22 MCP tools providing full task management API
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- Bidirectional sync with <5% data conflicts
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- <100ms response times under normal load
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### User Adoption Success 🎯
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- 80% of development work managed through new system
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- 70% reduction in context switching between tools
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- Team collaboration actively used for shared projects
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- Positive user feedback (4.5/5 satisfaction target)
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### Business Value Success 💰
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- 70% efficiency improvement in task management workflows
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- Single interface reducing tool management overhead
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- Enhanced AI integration improving development velocity
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- Foundation for future strategic planning web interface
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## Support & Documentation
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### Development Resources
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- **Implementation Guide**: [06-implementation-guides.md](planning/06-implementation-guides.md)
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- **Architecture Details**: [02-bmad-architecture.md](planning/02-bmad-architecture.md)
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- **API Reference**: MCP tools documentation (generated during development)
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### Integration Support
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- **Directus Instance**: https://enias.zeabur.app/admin
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- **MCP Server**: `tools/directus-mcp-server/` (existing + new tools)
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- **Task Master CLI**: Existing project with sync service
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- **Claude Code Agents**: Context integration through MCP tools
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### Project Management
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- **Planning Method**: BMad methodology with proven templates
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- **Task Tracking**: Task Master CLI (during development) → Directus (post-implementation)
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- **Progress Reports**: Weekly sprint reviews with stakeholder updates
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- **Issue Tracking**: GitHub issues for bug reports and feature requests
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---
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**Project Lead**: AI Assistant Development Team
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**Architecture Review**: Backend Architect & Network Security Architect
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**Implementation**: Python Expert Engineer & Code Quality Optimizer
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**Documentation**: Documentation Architect
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This project represents a strategic enhancement to the existing AI development ecosystem, providing the foundation for scalable, collaborative, and intelligent task management while maintaining compatibility with established workflows and tools. |