# Technical Requirements

## Data Architecture

**Core Collections:**
1. **tasks** - Primary task entity with rich metadata
2. **projects** - Project hierarchy and organization  
3. **task_statuses** - Customizable status definitions
4. **task_assignments** - User and AI agent assignments
5. **task_dependencies** - Task relationship management
6. **task_time_entries** - Time tracking and progress data
7. **task_templates** - Reusable task patterns

**Relationships:**
- Many-to-many: tasks ↔ projects, tasks ↔ users, tasks ↔ tags
- One-to-many: projects → tasks, task_statuses → tasks
- Self-referential: tasks → dependencies, projects → sub-projects

**Integration Collections:**
8. **task_ai_contexts** - AI agent context and prompt data
9. **task_bmad_workflows** - BMad methodology integration
10. **task_external_refs** - Links to Task Master, GitHub issues, etc.

## Performance Requirements
- **Response Time** - <100ms for basic CRUD operations
- **Scalability** - Support 10,000+ tasks across 100+ projects
- **Availability** - 99.9% uptime leveraging existing Directus infrastructure
- **Concurrent Users** - 50+ simultaneous users on Directus interface

## Security Requirements
- **Authentication** - Leverage existing Directus authentication system
- **Authorization** - Role-based access control for tasks and projects
- **Data Protection** - Encryption at rest using Directus security features
- **API Security** - Rate limiting and token-based authentication for API access
