Codeppr: Your AI-Powered Guardian Against Bad Commits

We've all been there. You're deep in the zone, cranking out code, solving problems left and right. You stage your changes, write a quick commit message, hit enter, and… suddenly realize you've just committed code with a critical bug, a security vulnerability, or a logic error that's going to haunt you during the next deployment. By then, it's already in your Git history, and you're scrambling to fix it with another commit.
What if there was a way to catch these issues before they ever make it into your repository? That's exactly why I built Codeppr – an AI-assisted code review agent that acts as your last line of defense during the pre-commit stage.

The Problem: Code Review Happens Too Late

Traditional code review workflows happen after you've already committed and pushed your code. Pull requests are fantastic for collaboration and catching issues, but they come with a fundamental limitation: the problematic code is already in your version control system. Even if reviewers catch issues, you're now dealing with additional commits to fix them, cluttering your Git history and potentially delaying your workflow.
For solo developers or small teams working on personal projects, formal code reviews might not happen at all. You're left relying entirely on your own vigilance, which – let's be honest – isn't foolproof, especially during late-night coding sessions or when you're context-switching between multiple features.

Enter Codeppr: AI Review at the Pre-Commit Stage

Codeppr takes a different approach by integrating AI-powered code analysis directly into your Git workflow through pre-commit hooks. Instead of reviewing code after it's committed, Codeppr analyzes your staged changes the moment you run git commit, giving you a chance to address issues before they ever enter your repository.
The workflow is beautifully simple:

1. You make changes to your code and stage them with git add
2. You run git commit as usual
3. Codeppr automatically intercepts the commit, analyzes your staged changes, and presents its findings
4. You review the AI's suggestions and choose whether to proceed with the commit or make corrections first

This seamless integration means you don't have to change your existing workflow or remember to run a separate tool. Codeppr becomes an invisible safety net that catches you when you need it most.

Intelligent, Categorized Feedback

One of Codeppr's standout features is its intelligent issue categorization. Rather than overwhelming you with a wall of suggestions, the tool organizes findings into three distinct priority levels:
Critical Issues are the showstoppers – things that will cause bugs, crashes, security vulnerabilities, or data loss. These are the issues that would wake you up at 3 AM if they made it to production. Think null pointer dereferences, SQL injection vulnerabilities, or race conditions that could corrupt your database.
High Priority Issues cover problems that are very likely to cause incorrect behavior or create hard-to-debug issues down the line. These might include logic errors, improper error handling, or algorithmic mistakes that would produce wrong results under certain conditions.
Low Priority Issues focus on maintainability, code quality, and best practices. While they won't break your application, they represent opportunities to improve code readability, performance, or adherence to established patterns.
This categorization helps you make informed decisions about how to proceed. Maybe you fix the critical and high-priority issues immediately but decide to create a follow-up task for the low-priority improvements. The power is in your hands.

Flexible AI Provider Support

Different developers have different preferences and requirements when it comes to AI models. Some prioritize cost, others value specific model capabilities, and many have existing relationships with particular providers. Codeppr respects this diversity by supporting three major AI providers out of the box:

• OpenAI (the default provider)
• Anthropic (including Claude models)
• Google Gemini

Setting up is straightforward. After installing Codeppr, you authenticate with your chosen provider:

codeppr auth login openai
# or
codeppr auth login anthropic
# or
codeppr auth login gemini

Switching between providers is just as easy:

codeppr use anthropic claude-sonnet-4-5-20250929

This flexibility means you can use the AI model that best fits your needs, budget, and preferences without being locked into a single ecosystem.

Getting Started: Installation and Setup

Getting Codeppr up and running in your project takes just a few minutes. The tool is distributed as a standard Python package, so installation is as simple as:

pip install codeppr

Once installed, navigate to your Git repository and initialize Codeppr:

codeppr install

This command sets up the necessary Git hooks that allow Codeppr to intercept your commits. Next, authenticate with your AI provider of choice:

codeppr auth login openai

That's it. You're now protected by AI-powered code review. The next time you commit, Codeppr will spring into action.

The Review Experience

When you run git commit with Codeppr installed, the tool displays the files that will be reviewed and presents you with options. You can choose to proceed with the AI review, skip it for this particular commit, or cancel the commit entirely.
If you proceed with the review, Codeppr analyzes your staged changes using the configured AI model. Within seconds, you receive categorized feedback highlighting potential issues. You can then decide whether to abort the commit to make fixes, or proceed if you're confident the flagged items aren't actually problems.
This interactive experience puts you in control while providing the safety net of AI analysis. You're never forced to accept or reject suggestions blindly – you make the final decision with the benefit of AI insights.

Why Pre-Commit Hooks Matter

The pre-commit stage is the perfect moment for automated code review. Your changes are fresh in your mind, you haven't yet moved on to the next task, and fixing issues requires only adjusting your staged changes rather than creating new commits.
By catching issues at this stage, Codeppr helps you maintain a cleaner Git history, reduce the back-and-forth in pull request reviews, and develop better coding habits through consistent, immediate feedback.

The Future of Code Quality

Codeppr represents a shift in how we think about code review and quality assurance. Rather than treating review as a post-hoc activity, we can integrate intelligent analysis directly into our development workflow, catching issues at the earliest possible moment.
The tool is open source and actively developed, with room for community contributions and feature enhancements. Whether you're a solo developer looking for an extra pair of eyes or part of a team wanting to establish baseline quality checks before formal code review, Codeppr offers a practical, unobtrusive solution.

Give It a Try

Codeppr is available now on PyPI and GitHub. Installation takes less than five minutes, and the tool requires no changes to your existing Git workflow. It simply adds an intelligent safety check at the moment you need it most.
Visit the GitHub repository to learn more, explore the source code, or contribute to the project. Your commits deserve a second look before they become permanent – let Codeppr provide it.
Because the best bugs are the ones that never make it into your repository in the first place.