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Awesome Reviewers

Ready-to-use system prompts for Agentic Code Review.
AwesomeReviewers.com »

Awesome Reviewers is an open-source registry of ready-to-use system prompts for agentic code review. Each “reviewer” prompt is distilled from thousands of real code review comments in leading open source repositories. These prompts capture best practices and coding standards that developers can easily apply during pull request reviews. Simply copy and paste a prompt into your AI coding agents (e.g. VS Code, Cursor, Claude, or any AI agent) to instantly get code review suggestions aligned with proven standards

📝 1K+ Reviewers   •   Popular OSS repositories   •   🚀 15+ Languages

Features

  • 🎯 1K+ Curated Prompts: Over 1,000 specialized review prompts covering many languages and frameworks. Each prompt is distilled from actual pull request comments, ensuring practical, actionable advice grounded in real code review scenarios.

  • 📊 Real Open-Source Insights: Every reviewer includes context from the open-source repository it came from, including a link to the source repo and stats like how many times that feedback appeared and the repos popularity. This transparency helps you trust the guidance its based on patterns that occurred in high-quality projects (e.g. a prompt might note 9 prior comments advocating a rule in a project with 16k on GitHub). In short, these AI prompts encapsulate community-agreed best practices.

  • Easy Integration: Using an Awesome Reviewer prompt is as simple as copy-pasting its text into your AI tool of choice. You can prepend the prompt as a system or agent instruction in chat-based coding assistants (like VS Codes AI extensions, ChatGPT, Cursor IDE, or Claude) to guide the AIs code review. The prompts are written to be IDE-ready no extra formatting needed. Just pick a prompt that matches your review focus (for example, “Never commit secrets” for a security review, or “Optimize memory access” for a performance review) and let your AI reviewer follow those guidelines.

  • 🔍 Searchable Library: Browse the entire library at awesomereviewers.com with fast search and filtering by category, language, or repository source. Each prompt shows origin repo, stats, and clear descriptions.

  • 🚀 One-Click Deployment: Deploy reviewer agents automatically on your PRs using Baz. The site includes a 🚀 Deploy to baz” button that lets you spin up the selected reviewer as an AI code review bot in a single click. Baz is a platform for agentic code reviews, and with this integration it can apply the Awesome Reviewers prompts to your PRs without any manual copy-paste. In other words, you get automated code review comments on your GitHub PRs based on the same proven guidelines (with no configuration needed beyond the click). This is a nod to how Awesome Reviewers works hand-in-hand with Baz to supercharge developer workflows.

  • 🏆 Community Leaderboard: Check out the new Leaderboard page to see the top contributors across all reviewer categories. Contributor stats are automatically regenerated by a GitHub Action on every deployment.

Getting Started

Using Awesome Reviewers is straightforward:

  1. Browse the Library: Visit awesomereviewers.com to view the list of available reviewer prompts. You can search or filter to find a prompt that fits your needs (e.g. “SQL Injection Check” under Security, or “Documentation consistency standards” under Documentation).

  2. Copy a Prompt: Click on a reviewer to view the full prompt text and guidelines. Copy the prompt text provided. Each prompt typically consists of a set of guidelines or rules that an AI should follow when reviewing code (written in clear, checklist-style instructions).

  3. Use in Your AI Tool: Paste the copied prompt into your AI code reviewer as a system message or initial instruction. For example:

    • VS Code: If using an AI extension (like GitHub Copilot Chat or ChatGPT VS Code extension), paste the prompt at the start of the conversation or as the system role content if supported.
    • Cursor (or other IDEs with AI chat): Provide the prompt in the tools AI chat before asking it to review your code/PR.
    • ChatGPT/Claude: Start a new chat, paste the prompt, then follow it with your code or description of the PR for review.

    The AI will then analyze your code changes according to the guidelines in the prompt, giving focused feedback (e.g. pointing out secret tokens in code if you used the Never commit secrets prompt, or checking for clarity and formatting if using a documentation prompt).

  4. Review AI Feedback: The suggestions from the AI should reflect the best practices from the prompt. You can iteratively refine your code with these suggestions. Feel free to combine multiple prompts or use different ones for different aspects of the review.

  5. (Optional) Deploy with Baz: If you use the Baz platform for CI, you can deploy a reviewer directly. Clicking “Deploy to baz” on a prompt will connect it with your Baz account, so that Bazs AI will automatically apply that reviewer to your future pull requests. This is ideal for teams wanting to enforce certain standards on every PR the reviewer agent will leave comments on your GitHub PR just like a human reviewer, but powered by the prompts rules.

No installation or CLI is required to use Awesome Reviewers the content is readily accessible. If you prefer not to use the website UI, you can also find all prompt files in the GitHub repos _reviewers/ directory for direct viewing or copying.

Acknowledgments

This project is maintained by the team at Baz as part of our mission to make Agentic code reviews accessible to every developer. The initial set of prompts was generated by analyzing countless code review comments across many repositories thanks to those open source communities for their feedback which formed the basis of these guidelines. We hope Awesome Reviewers helps you ship higher-quality code faster with a little help from AI. Happy coding and reviewing! 🚀

Disclaimer

Baz projects are community-contributed and while we strive to maintain high quality, we cannot guarantee the accuracy, completeness, or security of all library documentation. Prompts listed in this repo are inspired by their respective code owners, not by Baz. If you encounter any suspicious, inappropriate, or potentially harmful content, please open an issue in thie repo. We take all reports seriously and will review flagged content promptly to maintain the integrity and safety of our platform. By using Awesome Reviewers, you acknowledge that you do so at your own discretion and risk.

Languages
HTML 39.5%
JavaScript 32.8%
SCSS 21%
Python 5.1%
CSS 1.2%
Other 0.4%