How to Set Up Automated AI Code Reviews on GitHub (Step by Step)

Every pull request in your repo should be reviewed. But manual code reviews take time — often 2-4 hours per PR. And reviewers miss things when they are tired or rushed.

AI code review tools read every PR automatically and leave comments in minutes. Not replacing human reviewers — augmenting them. The AI catches the obvious bugs, the human reviewer focuses on architecture and business logic.

Here is how to set it up on GitHub. Three options — from easiest to most customizable.

Option 1: CodeRabbit (Easiest — 5 Minutes)

CodeRabbit is the most popular AI code review app on GitHub. Install it once, and every PR gets reviewed automatically.

Step 1: Install CodeRabbit

1. Go to coderabbit.ai
2. Click “Get Started Free”
3. Sign in with your GitHub account
4. Click “Add Repositories”
5. Select the repositories you want reviewed
6. Click “Install & Authorize”

That’s it. CodeRabbit is now installed.

Step 2: Open a Pull Request

Create any PR in your repository. Within 2-5 minutes, CodeRabbit will:

1. Post a summary — what the PR does, which files changed, potential impact
2. Leave inline comments — on specific lines with bugs, improvements, or concerns
3. Suggest fixes — with code you can apply with one click

Step 3: Configure (Optional)

Create .coderabbit.yaml in your repo root to customize the review:

# .coderabbit.yaml

language: "en"

reviews:
  # What to review
  profile: "assertive"  # Options: chill, assertive, followup

  # Request changes vs just comments
  request_changes_workflow: true

  # High-level summary
  high_level_summary: true
  high_level_summary_placeholder: "@coderabbitai summary"

  # Review specific paths
  path_filters:
    - "!**/*.md"        # Skip markdown files
    - "!**/*.txt"       # Skip text files
    - "!**/test/**"     # Skip test files (optional)

  # Auto-review when PR is opened
  auto_review:
    enabled: true
    drafts: false  # Don't review draft PRs

# Custom instructions for the AI reviewer
chat:
  auto_reply: true

Step 4: Interact with CodeRabbit

You can talk to CodeRabbit in PR comments:

@coderabbitai review           → Trigger a new review
@coderabbitai summary          → Get a PR summary
@coderabbitai resolve           → Resolve all CodeRabbit comments
@coderabbitai ignore this file → Stop reviewing a specific file

Pricing

• Free for open source repos
• Lite: $12/developer/month — basic reviews
• Pro: $24/developer/month — full features, custom instructions

Option 2: Claude GitHub App (Deepest Reviews)

If you use Claude Code, you can install Claude as a GitHub app that reviews your PRs.

Step 1: Install

Open a Claude Code session and run:

/install-github-app

Follow the prompts to connect Claude to your GitHub repository.

Step 2: How It Works

After installation, Claude automatically reviews every PR:

• Reads the full diff
• Understands the context of the changes
• Finds logic errors, security issues, and improvements
• Leaves detailed comments

Why Claude Reviews Are Different

CodeRabbit uses pattern matching + AI. Claude uses full reasoning. The difference:

CodeRabbit: "This function is missing error handling"
Claude:     "This function calls getUserById() which can return null,
             but line 45 uses it without a null check. If the user
             was deleted between the list fetch and detail fetch,
             this will crash with NullPointerException."

Claude understands the WHY, not just the WHAT.

Pricing

Requires Claude Pro ($20/month) or higher. Reviews consume your usage quota.

Option 3: GitHub Actions + AI (Most Customizable)

For full control, run AI reviews as a GitHub Action. You choose the model, the prompts, and the behavior.

Using the CodeRabbit GitHub Action

# .github/workflows/ai-review.yml

name: AI Code Review

on:
  pull_request:
    types: [opened, synchronize, reopened]

permissions:
  contents: read
  pull-requests: write

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - name: AI Code Review
        uses: coderabbitai/ai-pr-reviewer@latest
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
        with:
          debug: false
          review_simple_changes: false
          review_comment_lgtm: false

Add your OPENAI_API_KEY to repository secrets (Settings → Secrets → Actions).

Custom AI Review with Claude API

For maximum control, write your own review script:

# .github/workflows/claude-review.yml

name: Claude Code Review

on:
  pull_request:
    types: [opened, synchronize]

permissions:
  contents: read
  pull-requests: write

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - name: Get PR diff
        id: diff
        run: |
          git diff origin/${{ github.base_ref }}...HEAD > diff.txt
          echo "diff_size=$(wc -c < diff.txt)" >> $GITHUB_OUTPUT

      - name: Review with Claude
        if: steps.diff.outputs.diff_size > 0
        env:
          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
        run: |
          pip install anthropic
          python review.py

And the review script:

# review.py
import os
import anthropic

client = anthropic.Anthropic()

# Read the diff
with open("diff.txt") as f:
    diff = f.read()

# Ask Claude to review
response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=4096,
    messages=[{
        "role": "user",
        "content": f"""Review this code diff for a pull request.

Focus on:
1. Bugs or logic errors
2. Security issues
3. Performance concerns
4. Code style violations

Be specific. Reference file names and line numbers.
If everything looks good, say so briefly.

Diff:
{diff}"""
    }]
)

# Post as PR comment using GitHub API
review_text = response.content[0].text
os.system(f'gh pr comment ${{GITHUB_EVENT_PULL_REQUEST_NUMBER}} --body "{review_text}"')

This gives you full control over:

• Which AI model to use
• What to review (security, performance, style)
• How to present the review
• Cost management (only review certain file types)

Which Option to Choose?

My Recommendation

1. Start with CodeRabbit — install in 5 minutes, see immediate value
2. Add Claude for critical repos — deeper analysis on important projects
3. Build custom only if you need specific behavior that neither tool provides

Best Practices for AI Code Reviews

1. Don’t Replace Human Reviews

AI reviews catch bugs and patterns. Human reviews catch:

• Wrong business logic
• Architecture mismatches
• Missing requirements
• UX concerns

Best setup: AI reviews FIRST (in minutes), then human reviews what AI approved (focused on high-level concerns).

2. Customize the Review Focus

# .coderabbit.yaml — focus on what matters
reviews:
  path_filters:
    - "!docs/**"         # Skip documentation
    - "!**/*.test.*"     # Skip test files
    - "!*.json"          # Skip config files
    - "src/**"           # Only review source code

Don’t waste AI tokens reviewing auto-generated files, docs, or configs.

3. Add Project Context

Create a .github/CODERABBIT_INSTRUCTIONS.md or similar file:

# Review Instructions

This is a Kotlin Android app using:
- Jetpack Compose for UI
- MVI architecture
- Room for database
- Hilt for dependency injection

When reviewing, check for:
- StateFlow used instead of LiveData
- sealed interface for UI state
- No business logic in Composables
- Error handling on all API calls

AI reviews improve dramatically when they understand your project’s patterns.

4. Set Up Review Policies

# Require AI review before merge
reviews:
  request_changes_workflow: true  # AI can request changes, blocking merge

This prevents PRs from being merged if the AI found issues. Combined with branch protection rules, it ensures every PR gets reviewed.

5. Track Review Value

After a month of AI reviews:

• How many bugs did AI catch that humans missed?
• How much time did reviewers save?
• Are false positives (unnecessary comments) manageable?

If AI catches 2-3 real bugs per week, it pays for itself.

Quick Setup Checklist

For CodeRabbit (5 min)

• Go to coderabbit.ai → sign in with GitHub
• Install on your repositories
• Open a PR to test
• (Optional) Add .coderabbit.yaml for customization

For Claude GitHub App (5 min)

• Open Claude Code
• Run /install-github-app
• Authorize on GitHub
• Open a PR to test

For Custom GitHub Action (30 min)

• Create .github/workflows/ai-review.yml
• Add API key to repository secrets
• Create the review script
• Open a PR to test
• Adjust the prompt based on results

Quick Summary

Start today. Your first AI-reviewed PR will show you why every team should have this.

Related Articles

• Best AI DevOps Tools — AI review tools in the broader DevOps context
• Build Your First AI Agent — build your own review agent
• CLAUDE.md Guide — context files that improve AI review quality
• AI Test Generation — pair AI reviews with AI-generated tests