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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:

Copy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:

Copy/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

Copy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