Guide for GitHub
Integrate the AI Code Review Agent into your GitHub workflow.
Speed up code reviews by configuring the AI Code Review Agent with your GitHub repositories. In this guide, you'll learn how to set up the Agent to receive automated code reviews that trigger whenever you create a pull request, as well as how to manually initiate reviews using available commands.
The Free Plan offers AI-generated pull request summaries to provide a quick overview of changes. For advanced features like line-level code suggestions, consider upgrading to the 10X Developer Plan. For detailed pricing information, visit our Pricing page.
Video tutorial
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Installation and configuration steps
Follow the step-by-step instructions below to install the AI Code Review Agent using Bito Cloud:
Step 1: Log in to Bito
Log in to Bito Cloud and select a workspace to get started.
Step 2: Open the Code Review Agents setup
Navigate to the Code Review Agents setup page via the sidebar.
Step 3: Select your Git provider
Bito supports integration with the following Git providers:
GitHub
GitHub (Self-Managed)
GitLab
GitLab (Self-Managed)
Bitbucket
Since we are setting up the Agent for GitHub, select GitHub to proceed.
Step 4: Install the Bito app for GitHub
To enable pull request reviews, you need to install and authorize the Bito’s AI Code Review Agent app.
Click the Install Bito App for GitHub button. This will redirect you to GitHub.
On GitHub, select where you want to install the app.
Grant Bito access to your repositories:
Choose All repositories to enable Bito for every repository in your account.
Or, select Only select repositories and pick specific repositories using the dropdown menu.
Bito app uses these permissions:
Read access to code and metadata
Read and write access to issues and pull requests
Read access to organization members
Click Install & Authorize to proceed. Once completed, you will be redirected to Bito.
Step 5: Enable AI Code Review Agent on repositories
After connecting Bito to your GitHub account, you need to enable the AI Code Review Agent for your repositories.
Click the Go to repository list button to view all repositories Bito can access in your GitHub account.
Use the toggles in the Code Review Status column to enable or disable the Agent for each repository.
To customize the Agent’s behavior, you can edit existing configurations or create new Agents as needed.
Step 6: Automated and manual pull request reviews
Once a repository is enabled, you can invoke the AI Code Review Agent in the following ways:
Automated code review: By default, the Agent automatically reviews all new pull requests and provides detailed feedback.
Manually trigger code review: To initiate a manual review, simply type
/reviewin the comment box on the pull request and submit it. This action will start the code review process.
The AI-generated code review feedback will be posted as comments directly within your pull request, making it seamless to view and address suggestions right where they matter most.
Note: To enhance efficiency, the AI Code Review Agent is disabled by default for pull requests involving the "main" or "master" branches. This prevents unnecessary processing and token usage, as changes to these branches are typically already reviewed in release or feature branches. To modify this default behavior and include the "main" or "master" branches, you can use the Source or Target branch filter.
The AI Code Review Agent automatically reviews code changes up to 5000 lines when a pull request is created. For larger changes, you can use the /review command.
It may take a few minutes to get the code review posted as a comment, depending on the size of the pull request.
Step 7: Specialized commands for code reviews
Bito also offers specialized commands that are designed to provide detailed insights into specific areas of your source code, including security, performance, scalability, code structure, and optimization.
/review security: Analyzes code to identify security vulnerabilities and ensure secure coding practices./review performance: Evaluates code for performance issues, identifying slow or resource-heavy areas./review scalability: Assesses the code's ability to handle increased usage and scale effectively./review codeorg: Scans for readability and maintainability, promoting clear and efficient code organization./review codeoptimize: Identifies optimization opportunities to enhance code efficiency and reduce resource usage.
By default, the /review command generates inline comments, meaning that code suggestions are inserted directly beneath the code diffs in each file. This approach provides a clearer view of the exact lines requiring improvement. However, if you prefer a code review in a single post rather than separate inline comments under the diffs, you can include the optional parameter: /review #inline_comment=False
For more details, refer to Available Commands.
Screenshots
Screenshot # 1
AI-generated pull request (PR) summary
Screenshot # 2
Changelist showing key changes and impacted files in a pull request.
Screenshot # 3
AI code review feedback posted as comments on the pull request.
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