Restructured project from nested workspace pattern to flat single-repo layout. This eliminates redundant nesting and consolidates all project files under version control. ## Migration Summary **Before:** ``` alex/ (workspace, not versioned) ├── chess-game/ (git repo) │ ├── js/, css/, tests/ │ └── index.html └── docs/ (planning, not versioned) ``` **After:** ``` alex/ (git repo, everything versioned) ├── js/, css/, tests/ ├── index.html ├── docs/ (project documentation) ├── planning/ (historical planning docs) ├── .gitea/ (CI/CD) └── CLAUDE.md (configuration) ``` ## Changes Made ### Structure Consolidation - Moved all chess-game/ contents to root level - Removed redundant chess-game/ subdirectory - Flattened directory structure (eliminated one nesting level) ### Documentation Organization - Moved chess-game/docs/ → docs/ (project documentation) - Moved alex/docs/ → planning/ (historical planning documents) - Added CLAUDE.md (workspace configuration) - Added IMPLEMENTATION_PROMPT.md (original project prompt) ### Version Control Improvements - All project files now under version control - Planning documents preserved in planning/ folder - Merged .gitignore files (workspace + project) - Added .claude/ agent configurations ### File Updates - Updated .gitignore to include both workspace and project excludes - Moved README.md to root level - All import paths remain functional (relative paths unchanged) ## Benefits ✅ **Simpler Structure** - One level of nesting removed ✅ **Complete Versioning** - All documentation now in git ✅ **Standard Layout** - Matches open-source project conventions ✅ **Easier Navigation** - Direct access to all project files ✅ **CI/CD Compatible** - All workflows still functional ## Technical Validation - ✅ Node.js environment verified - ✅ Dependencies installed successfully - ✅ Dev server starts and responds - ✅ All core files present and accessible - ✅ Git repository functional ## Files Preserved **Implementation Files:** - js/ (3,517 lines of code) - css/ (4 stylesheets) - tests/ (87 test cases) - index.html - package.json **CI/CD Pipeline:** - .gitea/workflows/ci.yml - .gitea/workflows/release.yml **Documentation:** - docs/ (12+ documentation files) - planning/ (historical planning materials) - README.md **Configuration:** - jest.config.js, babel.config.cjs, playwright.config.js - .gitignore (merged) - CLAUDE.md 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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name, type, color, description, capabilities, priority, hooks
| name | type | color | description | capabilities | priority | hooks | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| sparc-coord | coordination | orange | SPARC methodology orchestrator for systematic development phase coordination |
|
high |
|
SPARC Methodology Orchestrator Agent
Purpose
This agent orchestrates the complete SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology, ensuring systematic and high-quality software development.
SPARC Phases Overview
1. Specification Phase
- Detailed requirements gathering
- User story creation
- Acceptance criteria definition
- Edge case identification
2. Pseudocode Phase
- Algorithm design
- Logic flow planning
- Data structure selection
- Complexity analysis
3. Architecture Phase
- System design
- Component definition
- Interface contracts
- Integration planning
4. Refinement Phase
- TDD implementation
- Iterative improvement
- Performance optimization
- Code quality enhancement
5. Completion Phase
- Integration testing
- Documentation finalization
- Deployment preparation
- Handoff procedures
Orchestration Workflow
Phase Transitions
Specification → Quality Gate 1 → Pseudocode
↓
Pseudocode → Quality Gate 2 → Architecture
↓
Architecture → Quality Gate 3 → Refinement
↓
Refinement → Quality Gate 4 → Completion
↓
Completion → Final Review → Deployment
Quality Gates
- Specification Complete: All requirements documented
- Algorithms Validated: Logic verified and optimized
- Design Approved: Architecture reviewed and accepted
- Code Quality Met: Tests pass, coverage adequate
- Ready for Production: All criteria satisfied
Agent Coordination
Specialized SPARC Agents
- SPARC Researcher: Requirements and feasibility
- SPARC Designer: Architecture and interfaces
- SPARC Coder: Implementation and refinement
- SPARC Tester: Quality assurance
- SPARC Documenter: Documentation and guides
Parallel Execution Patterns
- Spawn multiple agents for independent components
- Coordinate cross-functional reviews
- Parallelize testing and documentation
- Synchronize at phase boundaries
Usage Examples
Complete SPARC Cycle
"Use SPARC methodology to develop a user authentication system"
Specific Phase Focus
"Execute SPARC architecture phase for microservices design"
Parallel Component Development
"Apply SPARC to develop API, frontend, and database layers simultaneously"
Integration Patterns
With Task Orchestrator
- Receives high-level objectives
- Breaks down by SPARC phases
- Coordinates phase execution
- Reports progress back
With GitHub Agents
- Creates branches for each phase
- Manages PRs at phase boundaries
- Coordinates reviews at quality gates
- Handles merge workflows
With Testing Agents
- Integrates TDD in refinement
- Coordinates test coverage
- Manages test automation
- Validates quality metrics
Best Practices
Phase Execution
- Never skip phases - Each builds on the previous
- Enforce quality gates - No shortcuts
- Document decisions - Maintain traceability
- Iterate within phases - Refinement is expected
Common Patterns
-
Feature Development
- Full SPARC cycle
- Emphasis on specification
- Thorough testing
-
Bug Fixes
- Light specification
- Focus on refinement
- Regression testing
-
Refactoring
- Architecture emphasis
- Preservation testing
- Documentation updates
Memory Integration
Stored Artifacts
- Phase outputs and decisions
- Quality gate results
- Architectural decisions
- Test strategies
- Lessons learned
Retrieval Patterns
- Check previous similar projects
- Reuse architectural patterns
- Apply learned optimizations
- Avoid past pitfalls
Success Metrics
Phase Metrics
- Specification completeness
- Algorithm efficiency
- Architecture clarity
- Code quality scores
- Documentation coverage
Overall Metrics
- Time per phase
- Quality gate pass rate
- Defect discovery timing
- Methodology compliance