AI Code Review
Code Quality
Amartya Jha
• 16 February 2025
You’ve just finished writing a chunk of code. It looks good, it feels good, and you’re ready to push it to production. But then—bam—your app crashes. You spend hours debugging, only to realize you missed a tiny syntax error. Sound familiar?
Coding is like walking a tightrope. One wrong step, and everything comes crashing down. But what if you had a safety net? That’s where AI code checker tools come in. These tools are like your 24/7 available friends—they catch mistakes before they blow up, teach you better practices, and save you from endless debugging.
In this article, we’ll introduce you to 12+ AI code checker tools.
Let’s get started!
Why Use AI Code Checkers?
Manual code reviews are slow, tedious, and kinda soul-sucking. AI tools cut through the noise by automating all this work. Here’s why:
Catch mistakes early: AI checkers spot typos, syntax errors, and even potential security flaws while you code.
Learn best practices: These tools nudge you to follow style guides (PEP 8, anyone?) and write cleaner code.
Save time: Why waste hours debugging when AI can flag issues in seconds? Spend that extra time building cool features 🗿
Keep teams on the same page: No more “But I thought we used camelCase?!”. AI helps with consistency, making collaboration smoother and faster.
In short, AI code checkers aren’t just about fixing bugs—they’re about working smarter and learning faster.
Without further ado, let's jump onto seeing the tools. We have categorized the list into:
AI Code Checkers for Python
AI Code Checkers for Java
General Tools (Supporting multiple languages)
AI Code Checker Tools for Python
1. PyCharm
PyCharm isn’t just an IDE—it’s a powerhouse that includes an integrated AI code checker. With PyCharm, you get real-time code analysis, intelligent error detection, and helpful suggestions while you code.
Its built-in tools ensure that you not only write error-free code but also follow best practices.
Although it’s more than just a linter with its great code checking features.
Features:
Real-time error detection and smart code inspections
Intelligent code completion and automated refactoring
Integrated debugging, testing, and version control
Customizable inspection profiles to suit different project needs
2. Pylint
Pylint checks your Python code for mistakes before you even notice them, it is not AI-integrated but gives competition to AI code checker tools. It finds errors, catches bugs, and helps you follow the PEP8 style guide.
Although it might seem a bit picky at times, you can adjust its settings to match your project.
Features:
Detects a wide range of errors, from typos to logic issues
Enforces PEP8 standards for consistency
Provides detailed, actionable feedback and refactoring suggestions
Customizable settings to tailor checks to your project needs
3. Workik AI
Workik AI is one of the newer players in the Python code checking scene. This tool uses AI to not only identify errors but also suggest performance optimizations, making your code run more efficiently.
It’s especially handy when you’re looking to fine-tune your code’s performance while ensuring that it remains bug-free.
Features:
Real-time analysis to catch both syntax errors and performance bottlenecks
AI-driven suggestions for improving efficiency and code quality
Simple integration into your development workflow
Helps maintain optimized, high-performance code
4. Flake8
Flake8 is a lightweight, speedy code checker that combines the strengths of PyFlakes, pycodestyle, and the McCabe complexity checker.
It’s perfect if you want a tool that quickly spots common mistakes and style issues without overwhelming you with too much output.
Many developers love it for its simplicity and ease of use, especially when working on larger codebases with mixed coding styles. It is not an ai code checker tool, but a great code checker that should be in this list.
While not technically an AI-powered tool, there's another excellent code checker that deserves to be included in this list.
Features:
Fast detection of syntax errors and style violations
Integrates checks for code complexity (via McCabe)
Plugin-friendly to extend functionality (like checking for docstring styles)
Simple configuration that lets you easily toggle rules on/off
5. Jedi
Jedi goes beyond traditional linting by serving as an intelligent code assistant. It provides real-time autocompletion, static analysis, and handy “go to definition” features that can really speed up your workflow.
If you are refactoring or just trying to understand a large codebase, Jedi helps you understand your code better.
Features:
Intelligent auto-completion and code suggestions
Fast navigation with “go to definition” and code search
Supports refactoring to improve code structure
Works seamlessly with popular text editors and IDEs
6. Python Tutor
Python Tutor is perfect for those moments when you need to understand your code step by step. More than a code checker, it visually debugs your Python programs, making it easier to see exactly how your code is executed.
Features:
Step-by-step visual debugging to track code execution
Interactive code visualization that makes debugging fun
AI-powered explanations that help you grasp what’s happening behind the scenes
A great learning aid for beginners and seasoned developers alike
Now let’s move onto seeing the AI code checkers for Java.
AI Code Checker Tools for Java
7. DeepCode (acq by Snyk)
DeepCode uses machine learning to analyze your Java code and spot subtle bugs and potential design issues that might slip past manual reviews.
How to use it:
CI Integration: Connect DeepCode with your GitHub or Bitbucket repository so that every commit or pull request gets automatically scanned. This lets you catch problems early, before merging code into your main branch.
Dashboard Monitoring: Use its web dashboard to view detailed explanations of flagged issues and suggested fixes. This can help you learn the common pitfalls in your codebase over time.
Team Collaboration: Share reports with your team during code reviews to ensure everyone is on the same page about best practices.
Features:
Real-time scanning of your code
Detailed explanations and fix suggestions
Seamless integration with popular repositories and CI tools
8. Codacy
Codacy is a multi-language automated code review tool that works well with Java projects. It goes beyond simple linting to enforce coding standards and monitor code quality over time.
Some tips:
Automated Reviews: Set up Codacy to automatically review each pull request. This way, if a new piece of code violates your team’s coding guidelines, the merge can be blocked until it’s fixed.
Quality Metrics: Use Codacy’s scoring system to track your team’s progress. Regularly review trends in the code quality dashboard to identify areas that need improvement.
Custom Rules: Create Codacy’s rules to match your team’s preferred style. For example, you can enforce specific naming conventions or require unit test coverage for critical modules.
Features:
Supports many languages, including Java
Enforces coding standards and style rules
Provides quality metrics and trend reports
Easy integration with GitHub, GitLab, Bitbucket, and CI pipelines
9. Qodo
Qodo is an AI-powered code generation and review tool that helps you speed up Java development by suggesting code snippets and generating boilerplate code.
How to make it work for you:
Rapid Prototyping: Use Qodo to quickly generate parts of your code when starting a new feature. This can help you focus on business logic instead of repetitive setup tasks.
Unit Test Assistance: Let Qodo suggest unit test cases based on your code. This not only saves time but also improves the reliability of your application.
Code Reviews: Use its suggestions during code reviews to spot overlooked edge cases or to enforce best practices in your Java project.
Features:
Generates common code patterns and boilerplate
Suggests improvements for existing code
Integrates with your IDE for seamless real-time assistance
General Tools (Supporting Multiple Languages)
10. GitHub Copilot
GitHub Copilot acts like an AI pair programmer that works in many languages, including Java, Python, and JavaScript.
Usage advice:
Context-Aware Suggestions: As you type, Copilot offers full-line or block suggestions. For example, if you’re writing a function to parse XML in Java, it may suggest a complete method based on similar patterns seen in open-source projects.
Learning New APIs: Use it as a learning tool. When working with unfamiliar libraries, let Copilot suggest how to use the API, then cross-check with documentation.
IDE Integration: It works in VSCode and JetBrains IDEs—ensure you install the relevant plugin to get smooth integration.
Features:
Real-time code completion across many languages
Learns from vast amounts of public code
Reduces repetitive typing and speeds up coding
11. Intellicode
Microsoft’s Intellicode, built into Visual Studio and VSCode, gives you smart, context-aware code completions that adapt to your project’s style.
How to get the best out of it:
Customized Recommendations: Intellicode learns from your codebase, so the more you use it, the better its suggestions become. For example, it can suggest the most common variable names or method structures your team uses.
Efficiency Boost: Use it to speed up routine tasks like setting up loops or exception handling in your Java or C# projects.
Seamless Integration: Since it’s integrated directly into Visual Studio, you won’t need extra setup—just start coding and let it help you along the way.
Features:
Provides intelligent, context-based code completions
Learns from your existing code for personalized suggestions
Integrated directly into popular Microsoft IDEs
12. Sourcery AI
Sourcery is like having a personal AI code reviewer that works 24/7. Instead of waiting for code reviews from teammates, it gives real-time suggestions right inside your IDE or pull requests. Whether you're working solo or in a team, Sourcery helps catch errors early, improve code quality, and make your code more maintainable.
Why Use Sourcery?
✔ Fix issues before they break your code – Instant feedback on every pull request.
✔ Make your code cleaner & more readable – AI-powered refactoring makes it easier to maintain.
✔ Works inside your IDE – No need to switch tabs, it integrates seamlessly.
A Special Mention(+Winner😀): CodeAnt.ai
If you're serious about taking your coding skills to the next level you can try CodeAnt.ai! This smart tool fits right into your workflow by providing real-time analysis and actionable suggestions—just like the other tools we've discussed.
Here’s what makes CodeAnt.ai a great companion for developers:
Real-Time Feedback ⏱️: Get instant insights and suggestions as you code, so you can fix issues before they become bigger problems.
Seamless Integration 🔗: Works with popular IDEs and version control systems, meaning you don’t have to switch tools or disrupt your workflow.
Multi-Language Support 🌐: Whether you’re coding in Java, Python, or any other language, CodeAnt.ai adapts to your needs and helps maintain a cleaner codebase.
Smart Assistance 🤖: The AI learns from your coding style and projects, offering personalized tips that save you time and help improve overall code quality.
Boost Your Productivity 🚀: With automated code checks taking care of routine errors, you can focus more on building awesome features and less on manual reviews.
For a smoother, smarter coding experience, why not explore what CodeAnt.ai can do for you?
In Conclusion
We’ve covered a range of AI code checker tools that offer robust integration, multi-language support, and practical features to streamline your development process. Here is a mini checklist you can follow.
Language Support:
✔️ Does the tool support the programming language(s) you use?Real-Time Integration:
✔️ Does it provide live feedback in your IDE or during commits?Customization & Actionability:
✔️ Can you easily adjust its rules and get clear, actionable suggestions?
As if now, this was it. We will try to cover some more code-checker tools in our upcoming posts.
Thank you for reading.