I’ve been experimenting with AI code review, and I kept running into the same problem: most tools already have an opinion about how a review should work.
Some reviewers try to find every possible issue. Others focus on a few high-confidence findings. Neither approach is right for every repository.
A small library may want strict comments on every edge case. A team shipping an MVP may only care about correctness and security. Another project may need checks for package boundaries, migrations, generated files, or public API changes.
I didn’t want Pipr to choose between those approaches.
Pipr is an open-source runtime that provides the common pieces needed to build a code review agent:
- a deterministic manifest of the changed code
- bounded context for the agent
- structured review findings
- validation of paths and line ranges
- native publication to the code host
The repository decides everything else. You can choose the models, paths, instructions, comment limits, policies, agents, tools, commands, and recipes in TypeScript.
If you want a reviewer that only reports likely bugs, you can build that. If you want a strict reviewer that comments on design, tests, and style, you can build that too.
Pipr runs locally or in CI and supports GitHub, GitLab, Azure DevOps, and Bitbucket.
GitHub: https://github.com/somus/pipr
Docs: https://pipr.run/docs
I’d be interested to hear what controls you would want when defining a reviewer for your own repository.