Introducing lazyPR

I’ve always been frustrated by “lazy” pull request descriptions. You know the ones—“fix bug”, “update auth”, “refactor code”. They tell you almost nothing about what actually changed, why it changed, or what risks might be lurking in the diff.

After one too many code reviews where I had to manually parse hundreds of lines of diffs to understand what I was reviewing, I decided to build something better. Enter lazyPR.

What is lazyPR?

lazyPR is an AI-powered GitHub Action that rescues your repository from lazy documentation. Instead of relying on developers to write detailed PR descriptions (which they won’t), lazyPR analyzes the actual code changes and generates comprehensive summaries automatically.

But here’s what makes it different from other AI summarizers: lazyPR looks at the code, not just the commit messages.

The Problem with Traditional PR Reviews

Most teams face a familiar set of problems:

1. Vague PR titles and descriptions that require reviewers to manually inspect diffs
2. Ghost commits where the code doesn’t match what the commit message claims
3. No risk assessment to help prioritize which PRs need the most scrutiny
4. Inconsistent documentation across different team members

These problems compound as teams grow. A reviewer might spend 10-15 minutes just understanding what a PR does before they can actually review the code quality.

How lazyPR Solves This

1. Intelligent Summaries

lazyPR analyzes the actual diff content using multiple AI providers (OpenAI, Anthropic, or Gemini) to generate context-aware summaries. It doesn’t just parrot commit messages—it understands the code changes.

2. Ghost Commit Detection

This is one of my favorite features. lazyPR compares commit messages against the actual code changes in those commits. If someone writes “fixed authentication” but the diff shows they actually changed database schemas, lazyPR flags it as a potential ghost commit.

3. Automatic Risk Assessment

Every PR gets an impact score (0-100) and a risk label (Low, Medium, High). The scoring is based on:

• Files modified (sensitive files like auth, database, or core logic score higher)
• Lines of code changed
• Complexity of changes
• Pattern matching for risky operations

4. Bring Your Own Key

Unlike some services that charge per PR, lazyPR uses your own API keys. You have full control over costs and can choose which AI provider works best for your needs.

Technical Architecture

lazyPR is built as a Bun monorepo with three main packages:

• apps/github-action: The entry point that integrates with GitHub Actions
• packages/core: Diff fetching, sanitization, token management, and ghost detection
• packages/ai-engine: LLM orchestration, prompt engineering, and response parsing

The architecture prioritizes:

• Speed: Quick analysis even for large PRs
• Accuracy: Multiple providers for redundancy and best results
• Privacy: Your code stays in your infrastructure
• Flexibility: Configurable templates and custom prompts

Getting Started

Adding lazyPR to your repository takes less than 5 minutes:

# .github/workflows/lazypr.yml
name: lazyPR Summary
on:
  pull_request:
    types: [opened, synchronize]

jobs:
  summarize:
    runs-on: ubuntu-latest
    steps:
      - uses: elvis-ndubuisi/lazypr@v1
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}
          api_key: ${{ secrets.GEMINI_API_KEY }}
          provider: gemini  # or openai, anthropic
          template: default  # or concise, verbose, security

That’s it. From the next PR onward, you’ll have intelligent summaries automatically generated.

Real-World Impact

Since launching lazyPR, I’ve seen teams reduce their code review time by 30-40%. Reviewers can quickly understand what changed and focus their attention on the parts that matter most.

One team reported catching three critical issues in their first week—issues that might have been missed because they were buried in large diffs with vague descriptions.

What’s Next?

I’m actively working on several improvements:

• Multi-language support for teams using various programming languages
• Custom risk profiles for organization-specific sensitive files
• Integration with CI/CD for automated testing recommendations
• Team analytics to track documentation quality over time

Try It Out

lazyPR is available on the GitHub Marketplace and is completely free to use (you only pay for the AI API calls you consume).

If you give it a try, I’d love to hear your feedback. You can find me on X or open an issue on the GitHub repository.

---

Have you struggled with PR documentation in your team? What tools or processes have worked for you? I’d love to hear about your experiences in the comments or on X/Twitter.