What is the primary benefit of Copilot Flow Integration?

It combines Claude's reasoning and implementation skills with Copilot's massive codebase context for a more thorough, structured, and reliable development process.

Do I need the GitHub Copilot CLI installed to use this skill?

Yes, this skill uses a dedicated MCP server to interact with the GitHub Copilot CLI specifically for the design and review stages of the workflow.

Can I run specific stages of the workflow individually?

Absolutely. You can use specific slash commands like /copilot-flow:analyze or /copilot-flow:review to execute individual phases without running the full cycle.

How does the skill handle workflow interruptions?

The skill maintains state in a .claude/workflow-state.json file, allowing you to resume your task from the last completed stage if the process is interrupted.

Copilot Flow Integration

Name: Copilot Flow Integration
Author: Aykahshi

byAykahshi

•

생산성 및 워크플로

Orchestrates a structured 5-stage development workflow between Claude and GitHub Copilot to streamline analysis, architecture design, and implementation.

소개

This skill bridges the gap between Claude and GitHub Copilot by implementing a rigorous, automated lifecycle for software development. By leveraging an MCP server, it allows Claude to utilize Copilot’s extensive codebase context for architecture design and code review while handling implementation and requirements analysis itself. It is particularly useful for complex projects where end-to-end task management—from initial requirement breakdown to final delivery—is required within a unified, stateful environment.

주요 기능

GitHub Copilot CLI integration via MCP for massive token window analysis
2 GitHub stars
Specialized slash commands for both modular stage execution and full automation
Automated 5-stage collaboration workflow (Analyze, Design, Implement, Review, Deliver)
Persistent state management using local JSON to track progress and recover from errors
Structured output generation including architecture designs and code review reports

사용 사례

Large-scale codebase understanding and refactoring leveraging Copilot's context window
End-to-end feature development requiring architectural planning and rigorous code review
Standardizing AI-assisted development processes across complex software projects

소개

주요 기능

GitHub Copilot CLI integration via MCP for massive token window analysis
2 GitHub stars
Specialized slash commands for both modular stage execution and full automation
Automated 5-stage collaboration workflow (Analyze, Design, Implement, Review, Deliver)
Persistent state management using local JSON to track progress and recover from errors
Structured output generation including architecture designs and code review reports

사용 사례

Large-scale codebase understanding and refactoring leveraging Copilot's context window
End-to-end feature development requiring architectural planning and rigorous code review
Standardizing AI-assisted development processes across complex software projects