Getting started
The fastest way to try Rusty Bot is to drop the GitHub Action into your repo.
1. Add the workflow
Section titled “1. Add the workflow”Create .github/workflows/rusty-bot-review.yml:
name: Rusty Bot review
on: pull_request: types: [opened, reopened, synchronize, ready_for_review]
permissions: contents: read issues: read pull-requests: write
jobs: review: runs-on: ubuntu-latest steps: - uses: jegork/rusty-bot@v1 env: RUSTY_LLM_MODEL: anthropic/claude-sonnet-4-20250514 RUSTY_REVIEW_STYLE: balanced with: anthropic-api-key: ${{ secrets.ANTHROPIC_API_KEY }}2. Add the API key
Section titled “2. Add the API key”Under Settings → Secrets and variables → Actions, add ANTHROPIC_API_KEY
(or OPENAI_API_KEY / GOOGLE_API_KEY) — match the provider in
RUSTY_LLM_MODEL.
3. Open a PR
Section titled “3. Open a PR”That’s it. Rusty Bot will run on the next PR and post a structured review with a summary comment plus inline findings on the diff.
Pinning
Section titled “Pinning”| Pin | Behaviour |
|---|---|
@v1 | Floats to the latest 1.x.x release. Recommended. |
@v1.2.3 | Pinned to an exact release. |
@main | Tracks main. Use only for development. |
Pinning to a specific SHA is supported only for the action repo itself; the underlying Docker image is published per release tag.
Next steps
Section titled “Next steps”- Full GitHub Action reference — every input and env var, skipped event types, and how to pin the Docker image
- GitHub App (self-hosted) — run as a webhook server when you want one deployment to cover many repos
- Azure DevOps — drop the same review into Azure Pipelines with PR threads instead of GitHub comments
- LLM providers — swap to Azure OpenAI, an OpenAI-compatible endpoint, or any of 99+ providers via LiteLLM
- Convention files — teach the bot your house rules with a
REVIEW-BOT.mdchecked into the repo - Gating merges — fail the check on critical findings so PRs can’t merge until they’re resolved
- Tuning cost & noise — control how many files get the deep-review treatment vs. skipped outright