Build an AI Code Reviewer with OpenRouter

An AI code reviewer checks a Git change for bugs and security issues before you push or merge. Reviewers that only read the diff have to guess what the rest of the file looks like and whether a suspected bug actually fails at runtime, and their suggested fixes come back as text you copy in by hand. The reviewer in this guide uses the OpenRouter Responses API to run your changed files in a Linux sandbox, confirm each bug by running a check, and return fixes as patches you can apply with a flag. Across the four models we tested on a five-bug change, a review takes one to four minutes and costs between $0.015 and $0.045. A 233-line Python script (review.py) that uses only the standard library and runs locally, in a Git pre-push hook, or in GitHub Actions. Uploads the changed files, test files, and diff into a hosted Linux sandbox so the model can reproduce bugs and propose V4A patches. Every finding comes back marked confirmed (with the command and output that proved it) or unconfirmed (when a bug cannot be shown with a quick script). In our benchmarks on a five-bug change, Claude Haiku 5.5 averaged…