CodeRabbit now runs static analyzers, linters and provides one-click fixes for the issues identified. AI helps reduce the false positives and focus on the critical findings. CodeRabbit will respect the existing configuration files of these tools if they already exist in the project. For example, if your project already uses ruff and has a ruff.toml file at the root of the project, that will be used. In cases where project configurations are not found, CodeRabbit defaults will be used. Currently, CodeRabbit runs markdownlint, shellcheck, ruff, and languagetool. We will continue to add more tools. The default configuration can be changed through the .coderabbit.yaml file.

Are there any specific tools you'd like us to add? Let us know. We'd love to hear your suggestions!

Excited to announce that CodeRabbit is now GDPR compliant in accordance with EU regulations!

CodeRabbit now offers fixes for GitHub Check failures on pull requests. With this change, Check Runs on GitHub that add Annotations to Pull Requests will be used. For example, popular GitHub Actions published by reviewdog (action-golangci-lint, action-staticcheck, action-eslint) and super-linter among many others have the ability to report issues on Pull Requests as annotations. Checks that output logs will be supported shortly. CodeRabbit GitHub App requires permission to read Checks for this feature to work. To enable this, please grant the necessary permissions by visiting the CodeRabbit GitHub app settings under https://github.com/settings/installations. Support for GitLab will follow.

Excited to announce that CodeRabbit is now GDPR compliant in accordance with EU regulations!

CodeRabbit now offers a more comprehensive review of the markdown changes. In addition to the AI suggestions, we do a thorough check for spelling, grammar, word choice, language style, as well as improvements in paraphrasing and punctuation.

CodeRabbit now offers integration for self-hosted GitLab. Refer the documentation for the setup - https://docs.coderabbit.ai/integrations/self-hosted-gitlab

Working as recursive autonomous agent, CodeRabbit uses shell scripts to perform complex operations on the entire codebase, verifying changes and providing deeper insights.

Here are some uses cases :

• Want to defer implementing the CodeRabbit suggestion to a later time? Ask the bot the create an issue.

• Generate unit tests - comment @coderabbitai generate unit tests for the src/utils.ts

• In PR comments, ask the bot to gather insights on your repository including latest commits, frequently changed files, recent contributors etc

• When the CodeRabbit review comment is addressed, let the bot know and it can validate with the latest commit.

Really excited to see how this feature gets used, especially with access to the CLI commands. There are some suggestions in the pull request tips but we are looking forward to seeing additional use cases of how developers use this feature. Please consider sharing your experiences.

Enable Request Changes review workflow for CodeRabbit reviews via .coderabbit.yaml Yaml field request_changes_workflow (default: false). When enabled, review comments are posted as request changes and CodeRabbit review will be marked approved once all the review comments are resolved.

CodeRabbit can now learn from your conversations to fine-tune your reviews. If you encounter inaccurate feedback or something not relevant to your codebase, just let the bot know, and it will remember the context for the future. We understand that coding practices and standards evolve over time. Using the chat, you can inform the bot, and it will remove any existing learnings that are no longer relevant. This feature does not work, if you have opted out of data storage.

Verifies the reference of the changes on the overall codebase and identifies missing changes.

You can now integrate Jira and Linear into CodeRabbit. This would be used for additional context while reviewing pull requests. If you use any of these systems, we recommend you integrate CodeRabbit. We will be adding more integrations over time.

Identifies all issues affected by the code changes. This helps understand the impact on the overall product. It also assists in identifying duplicate issues or the impact on any other existing issues. This feature does not work, if you have opted out of data.

Issue Validation:

• CodeRabbit review can now assess the pull request changes against the linked GitHub or GitLab issue. Integration with other workflow systems including Jira and Linear is under development.
  
  
  

  

Code review comments:

• Review comments can now post committable suggestions that can be committed within the pull request with a single click.
  
  

  

Resolve Command:

• Use @coderabbitai resolve to mark all the CodeRabbit review comments as resolved all at once.

Introducing additional CodeRabbit commands for managing code reviews.

• Pause Reviews:

  • Use @coderabbitai pause in a PR comment to halt ongoing reviews.

• Resume Reviews:

  • Enter @coderabbitai resume in a PR comment to continue paused reviews.

• On-Demand Reviews:

  • Disable automatic reviews for your repository to switch to on-demand reviews.

  • Use @coderabbitai review in a PR comment. This command will override all review filters that might be set up in the repository settings and will initiate a one-time review.

• Help Command:

  • You can at any time post @coderabbitai help in a PR comment to get the list of all valid commands.

CodeRabbit customizations made easy! You can now customize CodeRabbit using a YML file from your repository. To learn more, refer to our comprehensive documentation on customizing CodeRabbit.

Path based instructions​

This section explains how to add custom code review instructions for the entire project or specific file paths in your project using glob patterns. Developers can provide tailored review guidelines based on the file paths. These instructions are needed only if you want the reviewer to follow specific instructions besides the standard review.

Overview​

Adding file path prompts allows developers to specify custom instructions for different parts of the codebase. For example, you may want to enforce style guide by file types or directories.

Sample Usage​

path: **/*.js

instructions: Review the javascript code against the google javascript style guide and point out any mismatches

path: tests/**.*

instructions: Review the following unit test code written using the Mocha test library. Ensure that: The code adheres to best practices associated with Mocha. Descriptive test names are used to clearly convey the intent of each test.

Notes​

• Paths accept glob patterns.

• Instructions generally work well for specific additional instructions. However, they are not that effective if you are instructing AI not to do something.

• Test the review feedback on pull requests and tailor as necessary.

CodeRabbit is now available for GitLab! We know many of you have been waiting for this integration. Thank you for your patience. Sign up for the free trial!