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Configure GitHub Copilot Custom Instructions for Better Code Generation

Job to be done: Configure GitHub Copilot custom instructions to guide its code generation based on project specifics

🇳🇬 Ways to use this in Nigeria

Ideas to get you started, adapt to your situation.

  • Entrepreneur

    Set up Copilot to generate React components for your startup's MVP that follow your design system's naming conventions and use Tailwind CSS, ensuring consistent UI development as you build.

  • 9-5 employee

    As a new developer, configure Copilot to generate code that adheres to your company's internal API standards and uses the approved logging framework, speeding up onboarding and reducing code review comments.

  • Student

    Configure Copilot to generate Python code for your final year project that strictly follows PEP 8 and uses the Django REST Framework, ensuring your project adheres to academic coding standards.

What you’ll get

A short setup that makes GitHub Copilot follow your project’s standards instead of blindly copying whatever patterns (including the bad ones) already exist in your code. You write a small “custom instructions” file once, and from then on Copilot’s suggestions match your style, conventions, and architecture. Think of it as onboarding a new teammate: tell it the rules up front and it stops guessing.

Tools you need

  • GitHub Copilot (freemium): the AI “pair programmer” that suggests code as you type in your editor. It has a free tier with monthly limits; heavier use is paid.
  • ChatGPT (freemium): used here to help you draft and refine the instructions.

Steps

  1. Understand the goal: without guidance, Copilot copies your repository’s existing habits, good and bad. Custom instructions tell it your conventions, your architecture, and the patterns to avoid, so it “colors inside your lines.”

  2. Draft the instructions with ChatGPT: get a first version by describing your project:

    Help me write custom instructions for GitHub Copilot for a [your project type, e.g.
a Python web app using Flask]. Cover: preferred coding style (e.g. PEP 8), key
architectural patterns to follow, libraries to prefer or avoid, common anti-patterns
in our codebase to steer clear of, and one or two examples of the code structure I want.
Keep it clear and concise.

    You should get a solid draft to refine. (“Anti-patterns” means common but bad ways of doing something.)

  3. Refine for your project: add your specifics, naming conventions, how you handle errors, how you talk to your database, anything that makes your codebase yours.

  4. Add the instructions to Copilot: the standard place is a file named .github/copilot-instructions.md in your repository. Create it and paste your instructions there; Copilot reads it automatically. (You can also set instructions in your editor’s Copilot settings.)

  5. Test and iterate: code as normal and watch Copilot’s suggestions. Do they match your rules? If not, tighten the wording or add a concrete example, and try again. It is a “write, test, refine” cycle.

Original source

Based on anchildress1’s DEV Community post “Everything I Know About GitHub Copilot Instructions, From Zero to Onboarded (For Real)”, sharing a method for writing effective Copilot instructions.

Notes & variations

  • Free-tier viability: Copilot’s free tier (with monthly limits) is enough to try this, and drafting the instructions with ChatGPT is free. Weigh the paid plan only if you use Copilot heavily.
  • Common pitfall: instructions that are too vague or too long. Copilot struggles with rambling, ambiguous directives. Be specific and focus on the rules that matter most.
  • Tip for better results: show, don’t just tell. A concrete example (a function signature, a class layout, your error-message format) guides Copilot far better than a description alone.

Keep going

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