GitHub Copilot Hackathon Challenge

[fernando79513]

🚀 GitHub Copilot Hackathon Challenge

https://github.com/Jfhelin/hack

Welcome to the GitHub Copilot Hackathon!
This challenge will guide you through the latest Copilot features — from Ask and Edit modes to MCP-powered issues, Copilot Coding Agent, and AI PR reviews.
You’ll work inside your own repository, experimenting freely and discovering how Copilot transforms your workflow.

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🧭 Phase 1 – Setup & Preparation

Goal: Get your environment and repository ready for Copilot experimentation.

🔹 1️⃣ Find or fork a project

• Pick a repository you’re comfortable working in — any language works.
  You can:

  • Use an existing project you maintain.
  • Fork a public repo (e.g. from GitHub Explore).

• Copy the markdown of this issue into your own issue in your working repo so that you can modify it.

• Create a new branch, e.g. copilot-hackathon.
  Keep all experiments in this branch — do not modify your main.

⚠️ Copilot never commits code without your consent, but keep your hackathon work isolated.

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🔹 2️⃣ Ensure GitHub Copilot is enabled

• Make sure the GitHub Copilot extension is installed and active in your IDE.
• Ensure you also have Copilot Chat available (and optionally Copilot Edits/Agent features if supported by your IDE).

📘 Documentation:

• Getting started with GitHub Copilot
• Setting up GitHub Copilot in VS Code

💡 You don’t need three separate installs — Copilot Chat and Edits are included in most IDE integrations.
Just verify both completions and chat are visible in your IDE.

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🔹 3️⃣ Configure the GitHub MCP server

We’ll use Copilot MCP to let Copilot Chat access your repo and issues.

• In your new branch, create a folder .vscode if it doesn’t exist.
• Inside it, create a file named mcp.json.
• Copy content from 👉 .vscode/mcp.json.
• Commit the file to your current branch.
• Observe and click the 'start' link on the top of the definition text in the mcp.json file.

📘 Learn more:
Understanding MCP and connecting Copilot to external resources

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💬 Phase 2 – Exploring Copilot Chat Modes

Goal: Learn how Copilot helps you explore, understand, and reason about your code.

🔹 4️⃣ Explore your code using Ask mode

Pick a file or function you don’t know well and experiment freely with Copilot Chat.

Try questions like:

• “Explain what this function does, step by step.”
• “Where is this class used?”
• “Could this function be simplified?”
• “Generate a test for this logic.”
• “Rewrite this using a different algorithm.”

💡 Be curious! Ask follow-ups. Ask why. Modify prompts.
Try Ask, Explain, Generate, and Edit modes to see how each behaves.

• Switch between models (e.g. GPT-5, Claud Sonnet 4.5, Claud Haiku 4.5) and compare reasoning quality.

📘 Use Copilot Chat to understand code

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🔹 5️⃣ Generate a copilot_instructions.md file

Copilot can generate project setup and context notes automatically — this file helps Copilot understand your project and coding style better.

💡 Why we’re doing this

The copilot_instructions.md file acts as a knowledge source for Copilot.
It summarizes:

• How the project is structured
• How to build and run it
• Key dependencies, conventions, and folders

When this file exists, Copilot can use it to reason more effectively about your codebase — for example, it can:

• Give more accurate answers when you ask questions about the project.
• Provide better suggestions for refactoring, debugging, and tests.
• Maintain consistent terminology and architecture decisions in its output.

Think of it as giving Copilot a “project briefing document”.

🧭 Steps

• Open the Command Palette (Ctrl/Cmd + Shift + P)
• Search for “Copilot: Generate Project Instructions”
• Follow the prompts to create a new file named copilot_instructions.md

Once it’s created, open the file and read what Copilot generated.
You can edit and expand this file — Copilot will use any updates in future conversations.

📘 Documentation:
Generate project instructions with Copilot

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🧩 Phase 3 – Working with Issues via MCP

Goal: Use Copilot’s MCP connection to explore, understand, and create issues.

🔹 6️⃣ Explore and discuss issues (via MCP)

Now that the github-remote MCP server is configured:

• Use Copilot Chat to list or summarize issues in your repo.
  Examples:
  • “List open issues in this repo.”
  • “Summarize issue Add some metadata to the desktop entry canonical/standup-timer#12.”
  • “Suggest next steps for this bug.”
  • “How could we improve code related to this issue?”

📘 Using GitHub Copilot in Issues

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🔹 7️⃣ Analyze code relevant to an issue

• Pick an interesting issue.
• Ask Copilot to locate where in the code this occurs, or to explain related logic.

Examples:

“Show me where this issue might occur in the code.”
“Explain how this module works.”
“What might cause this behavior?”

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🔹 8️⃣ Generate a new issue

Once you’ve discussed a potential change, ask Copilot Chat to create a new issue.

• “Generate a new issue proposing a refactor of this method.”
• “File an issue to add input validation.”

Let Copilot generate the issue content directly.

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🔹 9️⃣ Assign the new issue to Copilot Coding Agent

You can do this in two ways:

• In Copilot Chat, say “Assign this issue to the Copilot Coding Agent.”
• Or on GitHub.com → open the issue → click Assignees → select @copilot.

Observe how the Coding Agent interprets and plans the task.

📘 Copilot Coding Agent overview

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🧮 Phase 4 – Reviewing and Reflection

Goal: Use Copilot to review and reason about existing work.

🔹 🔟 Request a Copilot code review (on GitHub.com)

• Go to your repository on GitHub.com.
• Find an existing Pull Request (in your org’s main project or your own branch).
• Assign @copilot as a reviewer.

Copilot will analyze the diff and comment directly on the PR.

⚠️ This action updates the PR with Copilot’s review comments.
💡 Alternative: If you prefer, create a duplicate PR (from your hackathon branch) and assign Copilot there — this preserves the original untouched.

📘 Using Copilot for Pull Request reviews

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🧠 Optional – Share Your Insights

• What surprised you most about Copilot’s behavior?
• Did different models produce noticeably different results?
• Which feature felt most natural or valuable?

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✅ Completion Checklist

Step	Description	Done
1	Fork / create project branch	☐
2	Enable Copilot and Chat	☐
3	Add .vscode/mcp.json (in branch)	☐
4	Explore Ask mode + models	☐
5	Generate copilot_instructions.md	☐
6–9	Work with issues & Coding Agent	☐
10	Assign PR to Copilot for review	☐
✨	Share insights	☐

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Happy hacking and exploring Copilot! 🎉