Git AutoReview
Git AutoReview Team · Coding
Git AutoReview is an AI code review tool that reviews pull requests on GitHub, GitLab, and Bitbucket by running Claude, Gemini, and GPT against the same diff. What sets this automated code review setup apart is the approval gate: the models draft comments in VS Code, you pick which ones to keep, and only approved suggestions get published to the PR. It's built for developers and small teams who want a faster PR review tool without handing final judgment to a model.
About Git AutoReview
What Is Git AutoReview
Git AutoReview is a VS Code extension that plugs AI into your existing code review workflow. Instead of one model guessing at your changes, it runs two or three in parallel and shows you where they agree and where they don't. You stay in control of what actually lands on the pull request, which is the core of its human-in-the-loop code review design.
The tool exists because automated reviews have a trust problem. A 2024 study on automation bias found people accept AI output 96.8% of the time even when it's only right 18% of the time. That's a bad ratio. Git AutoReview's answer is a human approval gate: nothing publishes until a person signs off. It fits teams that want the speed of AI review without the risk of a model posting a confidently wrong comment.
The biggest tradeoff is cost structure. Git AutoReview doesn't bundle AI usage into its price. You bring your own Claude, Gemini, or GPT API keys, which adds roughly $2 to $5 per month on top of the subscription. In exchange, your code goes straight to your chosen provider and never touches Git AutoReview's servers. If you'd rather not deal with API keys at all, that's a real limitation, not a minor footnote.
Getting Started
- Install the free extension from the VS Code Marketplace and sign in with your account.
- Connect a repository from GitHub, GitLab, or Bitbucket and pick which cloud or self-hosted instance you use.
- Add your own API key for Claude, Gemini, or GPT so the models can run.
- Open a pull request, trigger a review, and read the draft comments inside the editor.
- Select the suggestions worth keeping and click Publish to PR. Only approved comments go live.
Product Information
A quick look at Git AutoReview's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Solo developers
- Small engineering teams
- Security-conscious teams
Tasks
- Reviewing large diffs
- Catching security issues
- Verifying acceptance criteria
Scenarios
- Teams on Bitbucket Server or Data Center
- Shops that want review consistency
- Solo projects on private repos
Key features
Multi-Model Review in Parallel
Git AutoReview runs Claude, Gemini, and GPT against the same diff and lets you compare the results. The three models only overlap on about 30% of findings, so running a multi-model AI code review surfaces issues a single-model tool would miss entirely. You can pick which models to use per review.
Human-in-the-Loop Approval
Every AI comment is a draft until you approve it. You review suggestions in VS Code, then edit, reject, or keep each one before anything is published to the pull request. No auto-publish path exists. A wrong AI comment can't reach your teammates by accident.
Broad Git Platform Support
The tool covers GitHub Cloud and Enterprise, GitLab Cloud and Self-Managed, and Bitbucket Cloud, Server, and Data Center, which means the same review workflow follows you across whichever platform each repository happens to live on. Bitbucket Server and Data Center support stands out, since many AI review tools leave those out. You can work across multiple platforms from one workspace.
Security Scanning
Two layers handle security: more than 20 built-in pattern rules plus a context-aware AI pass. Together they check for SQL injection, XSS, hardcoded secrets, and the OWASP Top 10 on every PR. It won't replace a full SAST suite. Think of it as a first pass.
Deep Review (Agent Mode)
For changes that need more than a quick scan, agent mode explores the full codebase. It reads related files, runs the linter, checks tests, and traces data flow. Expect two to five minutes per review. Use it on complex changes and the faster quick review on routine ones.
BYOK and Privacy First
You connect your own Claude, Gemini, or GPT API keys, so your code goes directly to your chosen provider. Git AutoReview stores no code on its servers. You pay your provider at cost with no markup. Costs stay predictable, and vendor lock-in drops off the table.
Config File and Review Profiles
A .gitautoreview.md file in the repo root holds team-wide review rules, versioned in git alongside your code. Review profiles let you switch between named setups for models, keys, prompts, and rules from the status bar in one click. Both keep review behavior consistent across a team.
Pros and cons
Pros
- Three models in parallel catch issues a single-model reviewer skips, since overlap is low.
- The approval gate means no AI comment reaches a PR without a human signing off.
- Flat per-team pricing is far cheaper than per-user competitors for teams of any size, and a solid CodeRabbit alternative on cost.
- Bitbucket Server and Data Center support covers platforms many rivals ignore.
- BYOK routing keeps code off Git AutoReview's servers and costs at provider rates.
Cons
- You need your own API key, which adds roughly $2 to $5 per month and a setup step some users won't want.
- Model quality and speed depend on which provider you connect, so results vary between teams.
- It runs inside VS Code, so developers who work in other editors can't use it.
- Free tier caps at 10 reviews a day and one repository, tight for anything beyond casual use.
Frequently asked questions
It's an AI code review tool that scans your pull requests on GitHub, GitLab, and Bitbucket, drafts review comments with Claude, Gemini, and GPT, and lets you approve which ones publish. You get AI help without giving up the final say on what lands.
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