AI collaboration workflow plugin - Implements automated collaborative development process between Claude and Copilot through structured 5-stage workflow
Content & Writing
85 Stars
2 Forks
Updated Jan 19, 2026, 04:39 AM
Why Use This
This skill provides specialized capabilities for aiskillstore's codebase.
Use Cases
Developing new features in the aiskillstore repository
Refactoring existing code to follow aiskillstore standards
Understanding and working with aiskillstore's codebase structure
---
name: copilot-flow
description: AI collaboration workflow plugin - Implements automated collaborative development process between Claude and Copilot through structured 5-stage workflow
license: MIT
---
# Copilot Flow Integration
When to use this skill:
- When you need a structured AI-assisted development workflow
- When you want to leverage both Claude and Copilot's strengths
- When you require end-to-end task management from analysis to delivery
**Triggering conditions:**
- When user mentions "請 Copilot 協助" (Please ask Copilot to assist)
- When user says "詢問 Copilot" (Ask Copilot)
- When user requests "執行 copilot-flow" (Execute copilot-flow)
- When user starts with "copilot-flow:" or "c-flow:" prefix
## Core Features
This skill orchestrates a complete 5-stage AI collaboration workflow:
1. **Analyze** (Claude) - Requirements analysis and structuring
2. **Design** (Copilot) - Architecture design and planning
3. **Implement** (Claude) - Code implementation based on design
4. **Review** (Copilot) - Code quality assessment
5. **Deliver** (Claude) - Final integration and documentation
## Workflow Commands
The workflow is managed through specialized slash commands in the `/commands` directory:
### /copilot-flow:analyze [task description]
- Executes the analysis phase
- Claude analyzes requirements and prepares structured prompts
- Output: `analysis-result.md`
### /copilot-flow:design [goals]
- Executes the design phase using Copilot MCP
- Creates architecture design based on analysis
- Output: `architecture-design.md`
### /copilot-flow:implement [target]
- Executes implementation phase
- Claude implements code following Copilot's design
- Output: Source code files and `implementation-report.md`
### /copilot-flow:review [scope]
- Executes review phase using Copilot MCP
- Professional code review with focus areas
- Output: `code-review-report.md`
### /copilot-flow:deliver [objectives]
- Executes final delivery phase
- Claude integrates all results and documentation
- Output: Complete delivery package
## Usage Patterns
### Full Workflow Execution
For complete task execution, use the workflow orchestrator:
```
執行 copilot-flow 實現用戶認證系統
```
This will:
1. Show preview of all stages
2. Wait for confirmation
3. Execute each stage in sequence
4. Manage state between stages
5. Provide final delivery package
### Individual Stage Execution
Execute specific stages independently:
```
/copilot-flow:analyze 分析現有代碼庫並提出改進建議
/copilot-flow:review 審查 auth.js 檔案的安全性
/copilot-flow:implement 根據設計文檔實現 API 端點
```
## State Management
The workflow maintains state through:
- `.claude/workflow-state.json` - Current stage and progress
- Stage output files - Results from each phase
- claude-mem integration - Complete interaction history
## AI Model Collaboration
### Claude Responsibilities
- Requirements analysis and structuring
- Code implementation and modifications
- Final integration and delivery
- File system operations
### Copilot Responsibilities (via MCP)
- Architecture design recommendations
- Code quality review and feedback
- Security and performance assessment
- Best practices guidance
## Example Workflow
### User Request
```
執行 copilot-flow 實現一個 REST API 進行用戶認證,支持 JWT token
```
### Workflow Execution
1. **Preview Mode** - Shows planned stages and estimated time
2. **Analysis** - Claude breaks down requirements
3. **Design** - Copilot suggests architecture
4. **Implementation** - Claude writes code
5. **Review** - Copilot reviews implementation
6. **Delivery** - Claude prepares final package
### Outputs
- `analysis-result.md` - Structured requirements
- `architecture-design.md` - System design
- Source code files - Implementation
- `code-review-report.md` - Quality assessment
- `delivery/` - Complete package with docs
## Best Practices
### Do
- Start with clear requirements
- Let the workflow handle stage transitions
- Review each stage output before proceeding
- Use full workflow for complex tasks
- Execute individual stages for specific needs
### Don't
- Skip stages in full workflow mode
- Modify intermediate files manually
- Run stages out of sequence
- Ignore review recommendations
## Error Recovery
If workflow is interrupted:
1. Check `.claude/workflow-state.json` for current state
2. Resume from last completed stage
3. Or restart from specific stage
4. All progress is preserved
## Integration with Other Skills
- **copilot-mcp-server**: Used internally by design and review stages
- **claude-mem**: Records all workflow interactions
- File system tools: Used by Claude for implementation
## Keywords
AI collaboration, workflow, automation, Claude, Copilot, structured development, end-to-end, project management, code review, architecture design