AI Tools ~10 hours to build

AI Code Reviewer Bot

Your tireless code reviewer that never misses a bug.

The Problem

Code reviews are a bottleneck. Senior developers spend hours reviewing PRs, often catching the same issues repeatedly: missing error handling, security vulnerabilities, style inconsistencies. Meanwhile, junior devs wait days for feedback, and bugs slip through when reviewers are rushed or tired.

The Solution

A GitHub bot that automatically reviews every PR using AI. It catches common bugs, security issues, and code smells instantly—before human reviewers even look at the code. Humans focus on architecture and logic; the bot handles the tedious stuff.

How it works:

1

Install GitHub App

One-click install on your repos

2

Open a PR

Bot reviews automatically

3

Get inline comments

Suggestions right on the diff

Market Research

AI code review is hot. GitHub Copilot proved developers will pay for AI tools. Existing players like CodeRabbit and Sourcery show market demand, but there's room for simpler, more affordable alternatives.

GitHub has 100M+ developers—massive potential market
Code review is 2nd most time-consuming dev activity after coding
CodeRabbit raised $2M—validates market demand

AI Prompts to Build This

Copy and paste these into Claude, Cursor, or your favorite AI tool.

1. Project Setup

Create a Next.js app for an AI Code Reviewer GitHub App. The app needs: - GitHub App OAuth flow for installation - Webhook endpoint to receive PR events - Dashboard showing: installed repos, recent reviews, settings - Landing page explaining the product with "Install" CTA Use Probot library to simplify GitHub App development. Set up webhook handling for pull_request.opened and pull_request.synchronize events.

2. Core Feature

When a PR webhook is received: 1. Fetch the PR diff using GitHub API 2. For each changed file, send to Claude/GPT-4 with this prompt: "Review this code diff. Identify: bugs, security issues, performance problems, and style issues. For each issue, specify the line number and provide a suggested fix." 3. Parse the AI response and create GitHub review comments on specific lines 4. Post a summary comment with overall assessment Handle rate limits and large PRs by chunking files.

3. Configuration

Add per-repo configuration via .ai-reviewer.yml file: - review_focus: ["security", "performance", "style"] - what to check - ignore_patterns: ["*.test.js", "vendor/*"] - files to skip - severity_threshold: "warning" - minimum severity to comment - auto_approve: false - whether to approve clean PRs Parse this config on each review and adjust AI prompt accordingly.