GitHub offers several AI tools under the Copilot umbrella that cover your entire development workflow. Copilot can provide an AI-powered code review shortly after you open a pull request on GitHub. Rather than waiting for a teammate, you can add Copilot as a reviewer to receive context-aware feedback. With access to your entire codebase, it delivers actionable suggestions that you can apply in just a few clicks:
Pull requests are the standard collaborative workflow provided by GitHub and similar services like GitLab to facilitate code review for projects managed with Git. A pull request, or a PR for short, is a formal request to merge code from one branch—or fork—into another, and it’s where code review typically happens.
In practice, code review isn’t always timely or consistent. Some reviewers approve pull requests immediately without much scrutiny, while others leave long lists of minor nitpicks. It can also be difficult to find someone with the right level of experience or enough context about a specific part of the codebase. These issues are common in open-source projects as well, where reviews depend on the limited time of volunteer maintainers.
In this tutorial, you’ll learn how to leverage GitHub Copilot for AI-assisted code review in pull requests and how to integrate it into your workflow to get faster, more structured feedback. Whether you’re working on a commercial project or contributing to an open-source one, Copilot can help you catch issues early and improve your code before it’s merged.
Think of Copilot’s review as a fast first pass. It can reliably flag correctness mistakes and regressions to documented behavior, often before a human reviewer has even opened the PR.
Prerequisites
Before you get started with AI-assisted code reviews, make sure you have the following in place:
- Git and GitHub Knowledge: You should have a basic familiarity with Git and GitHub, including how to create branches, commit changes, and open pull requests.
- Git Client and GitHub CLI: You should have the
gitclient configured in your command line. Additionally, you’ll need the GitHub CLI tool, as it simplifies common GitHub-related tasks. Make sure you’re running v2.88.0 or later, which introduced support for requesting Copilot code reviews from the command line. - GitHub Account: You need a GitHub account with a paid Copilot plan (Pro, Pro+, Business, or Enterprise). To check your subscription status, visit GitHub Copilot settings.
Depending on how you use GitHub, you may already have access to GitHub Copilot through your organization. Sometimes, you may qualify for Copilot under special conditions.
For example, if you’re a student or a teacher, or if you regularly contribute to a popular open-source project, then you might be eligible for free access to GitHub Copilot Pro. Check out GitHub Education to learn more. Keep in mind that GitHub reassesses whether you qualify for free access on a monthly basis.
But even on the free plan, you can still try out Copilot’s code review feature for 30 days at no cost. Just subscribe to GitHub Copilot Pro and cancel before the first billing cycle begins. The trial period is a one-time offer per account, so you won’t be able to start another one after the first one ends.
Note: At the time of writing, GitHub has temporarily paused new paid subscriptions for Copilot due to exceptionally high demand and the associated infrastructure costs. You can read the official announcement on GitHub’s blog to learn more.
To follow along with this tutorial, you’ll also need a GitHub repository where you can freely create branches and pull requests. Although you can create a new repository from scratch or import one from another Git-based hosting service, the quickest option is to download the provided supporting materials. They include a small, hands-on project you’ll be working on:
Get Your Code: Click here to download the free sample code you’ll use to practice AI-assisted code review on a sample FastAPI pull request with GitHub Copilot.
Take the Quiz: Test your knowledge with our interactive “How to Use GitHub Copilot Code Review in Pull Requests” quiz. You’ll receive a score upon completion to help you track your learning progress:
Interactive Quiz
How to Use GitHub Copilot Code Review in Pull RequestsTest your knowledge of GitHub Copilot code review in pull requests, including custom instructions and automatic reviews.
The sample project is a real-time quiz application inspired by Kahoot! and Mentimeter, featuring a FastAPI backend and a mobile-first JavaScript, HTML, and CSS frontend. It allows you to make your own quizzes from scratch—and store them in the human-readable YAML format—or generate a random quiz on the fly using ChatGPT’s API:
Each player is assigned a randomly generated name with an emoji, such as 🐯 Grumpy Tiger, 🦨 Gentle Skunk, or 🐮 Lazy Cow, to keep things light and fun. You can start the server on a local network and have your friends or family connect from their mobile devices using a QR code or a PIN.
Are you ready to dive in?
Step 1: Request a Code Review From GitHub Copilot
If you haven’t already, go ahead and grab the supporting materials. The sample Git repository includes a feature branch with intentional code issues that GitHub Copilot can catch when you request a review. For reference, you’ll also find another branch with the completed code to explore at your own pace:
Get Your Code: Click here to download the free sample code you’ll use to practice AI-assisted code review on a sample FastAPI pull request with GitHub Copilot.
After downloading the materials, upload the local pop-quiz repository—including all branches—to your GitHub account. This will create a remote copy of the repository for your own experimentation. There are several ways to accomplish this. Although you can handle most tasks through the GitHub web interface, the GitHub CLI is often faster and more convenient.
One straightforward approach is to use the GitHub CLI (gh) alongside standard git commands. This allows you to create the repository and push all branches in just two steps once you’re in the downloaded pop-quiz/ directory:
