Automated review is most useful when teams can adapt it to their own repositories and model choices—not when it dictates a single workflow. This project makes that flexibility central: teams can run review assistance in their existing Git platform and retain control over deployment, prompts, and model selection.
What Sets It Apart
- Its
/review,/improve,/describe, and/askcommands cover distinct stages of a pull request, from understanding a change to surfacing potential issues and proposing improvements. - Support for GitHub, GitLab, Bitbucket, Azure DevOps, and Gitea lets teams avoid changing hosting platforms to add AI-assisted review.
- LiteLLM-compatible model options make it possible to switch among hosted providers and local deployments, reducing dependence on a single model vendor.
- Self-hosting and configurable prompts offer control over data handling and review behavior, while also making setup and ongoing maintenance the team's responsibility.
Who It Suits—and the Trade-off
Great fit if your team wants customizable, model-flexible review automation inside an existing pull-request workflow and is prepared to manage its own credentials and deployment. Look elsewhere if you need a fully managed review service, guaranteed correctness, or a substitute for human review: generated feedback still needs verification, and results depend on the selected model and configuration.
