Kilo | Code Reviewer
33
Overview
- Eliminate post-merge bugs and security vulnerabilities by catching them in your IDE before committing, using the local code review feature that provides real-time feedback on uncommitted changes.
- Reduce human reviewer workload and accelerate pull request cycles with automated analysis of every new pull request that detects bugs, performance issues, and style violations.
- Enforce your team's specific coding standards and architectural patterns consistently, as the AI learns from custom instructions and adapts to your preferences over time.
- Choose the depth of analysis that fits each review, from cost-effective routine checks to deep inspections, by selecting from AI models like Claude 4 Opus or Gemini 2.5 Pro.
- Focus reviews on what matters most for your project by customizing the review style (strict, balanced, lenient) and priority areas like security, performance, or test coverage.
- Maintain full codebase security with read-only access that allows the tool to analyze your GitHub or GitLab repositories without making any changes.
Pros & Cons
Pros
- Scrutinizes new pull requests
- Detailed feedback
- Detects potential issues
- Security threats analysis
- Performance difficulties detection
- Style violations checks
- User-determined settings
- Comment-based suggestions
- Issues rectification code examples
- Easy setup process
- GitHub integration
- GitLab integration
- Review style customization
- Review focus settings
- Custom instructions input
- Local code reviews capability
- Real-time feedback
- Productivity increase
- Post-merge issues reduction
- Free with certain models
- IDE integration
- Continuous learning facilitation
- Secure operations
- Pull requests automatic identification
- Readable and actionable feedback
- Guided by predefined parameters
- Documentation review
- Test coverage analysis
- Enforces coding standards
- Local code review in IDE
- Inline comments on PR
- State-of-the-art models
- Strict, balanced, lenient review styles
- Supports coding architectural patterns
- Trusted by 1.4M+ developers
- Read only access
- Potential bugs identification
- Security vulnerabilities detection
- Code quality issues detection
- VS Code integration
- JetBrains integration
- Eliminates easy-to-catch bugs
- Prevents failed CI pipelines
- Cloud Agents integration
- IDE Extensions
- App Builder integration
Cons
- No Bitbucket integration
- No multiple platform support
- Requires manual setup
- No automated learning
- No standalone application
- No team collaboration features
- Doesn't support all IDEs
- Unknown cost with certain models
Reviews
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❓ Frequently Asked Questions
Kilo Code Reviewer is an AI-powered tool utilized for reviewing and analyzing code. It automatically reviews new pull requests and offers detailed feedback based on the analyzed code. It comes with the capability of detecting bugs, security threats, performance difficulties, and style violations. The tool makes it convenient for developers to make adjustments before the code undergoes a human review.
Kilo Code Reviewer analyzes code via its AI models. It examines new pull requests, scrutinizes changes, and checks for potential issues including bugs, security threats, performance problems, and style violations. The focus and detail of the review can be customized based on user determined settings.
Kilo Code Reviewer can detect a variety of issues. These include bugs, security threats, performance difficulties, and style violations. The detection and focus of these issues can be adjusted based on the settings determined by the user.
Kilo Code Reviewer provides feedback in the form of inline comments on pull requests. These comments contain specific suggestions, explanations, and code examples to help rectify detected issues. This feedback mechanism allows developers to address issues before the code undergoes a human review.
Yes, Kilo Code Reviewer can be easily integrated with GitHub and GitLab. Users can connect their repositories with these platforms in just one click, making it an efficient tool for any project undergoing development on these platforms.
Setting up Kilo Code Reviewer is a simple four-step process. Firstly, connect your GitHub or GitLab repository. Secondly, choose a suitable AI model for code analysis from available models. Thirdly, set your review style and focus, deciding how detailed the reviews should be and what the main focus of i.e. security, performance, bugs etc. should be. Fourthly, add custom instructions to tell the AI about specific coding standards or areas of importance to observe.
Yes, Kilo Code Reviewer allows users to input custom instructions. Users can tell the AI about their coding standards, architectural patterns, or specific things to watch for. The AI is designed to learn and adapt to team's preferences over time.
Yes, Kilo Code Reviewer supports local code reviews. It can review changes locally in user's Integrated Development Environment (IDE) even before the code is committed. It thus provides instant feedback on uncommitted changes, enabling catching of issues before the code reaches the repository.
Kilo Code Reviewer mitigates potential post-merge issues by identifying and rectifying coding issues before they reach the code repository. By offering real-time feedback on pull requests and even uncommitted changes, it allows developers to address these issues early in the development cycle. This reduces the chances of any post-merge issues.
Yes, Kilo Code Reviewer is available for free with certain AI models, such as the MiniMax M2.1 or the GLM 4.7 models. It allows unlimited AI-powered code reviews when these models are used.
Kilo Code Reviewer allows users to choose from a variety of AI models for code analysis. These include state-of-the-art models like Claude 4 Opus for a deeper analysis and cost-effective options like Gemini 2.5 Pro for routine reviews.
Yes, users can set the focus and style of their code reviews with Kilo Code Reviewer. They can adjust how thorough the reviews should be (strict, balanced, or lenient), and choose what to emphasize (security, performance, bugs, code style, test coverage, or documentation).
Yes, Kilo Code Reviewer automatically detects and reviews new pull requests. The system scrutinizes changes in these requests and provides actionable feedback to help rectify detected issues.
Yes, Kilo Code Reviewer can catch bugs before the code reaches the repository. It offers real-time feedback on uncommitted changes in the user's IDE, thus enabling potential bugs, security vulnerabilities, and code quality issues to be addressed early in the development process.
Kilo Code Reviewer integrates seamlessly with a user's Integrated Development Environment (IDE). It allows local code reviews within the IDE, providing real-time feedback on uncommitted changes. This review can be run directly in VS Code or JetBrains giving instant feedback without leaving the editor.
Kilo Code Reviewer is highly adaptable and can integrate with several popular coding platforms. Specific platforms include GitHub and GitLab, with Bitbucket integration also in the pipeline.
The real-time feedback from Kilo Code Reviewer is provided in the form of inline comments on pull requests. It gives specific suggestions, explanations, and code examples to address any issues discovered in the code. This gives developers an opportunity to learn from these comments and implement necessary changes before the code undergoes a human review.
Kilo Code Reviewer increases developer productivity by streamlining the code review process. By catching bugs and other issues early in the development cycle, it reduces the time wasted in fixing post-merge problems. It also enforces coding standards consistently and provides learning opportunities from review suggestions which leads to continual improvement in coding standards and thus productivity.
Kilo Code Reviewer's code reviews are AI-powered as they utilize cutting-edge AI models to analyze the code. This AI technology can review code at a deeper level, recognize and learn coding patterns, monitor user-defined focus areas such as security or performance, and adapt to a team's preferences over time. Furthermore, it can detect bugs, security threats, performance issues, as well as style violations, providing instructive feedback to assist in their rectification.
Kilo Code Reviewer supports different review styles by allowing users to customise the level of thoroughness in their reviews. The review style can be set to strict, balanced, or lenient. The tool also allows users to direct the AI's focus towards specific areas they are interested in such as security, performance, bugs, code style, test coverage, or documentation.
Kilo Code Reviewer is an AI-based tool that provides automated reviews and analyses of code. It inspects pull requests automatically, offering complete feedback derived from the evaluated code. The tool checks for possible problems such as bugs, security risks, performance issues, and style infringements according to user's specified settings. It allows developers to make improvements before the code undergoes a human review. Kilo Code Reviewer supports comment-based recommendations, elucidations, and code examples to aid in rectifying problems. The tool is flexibly designed for easy setup, allowing users to link with platforms like GitHub or GitLab, select appropriate AI models for analysis, set the review style and focus, and provide custom instructions for code inspection.
Kilo Code Reviewer benefits from artificial intelligence to automatically inspect new pull requests and deliver detailed feedback derived from code analysis. By using AI, the tool provides thorough, accurate and instant feedback, pinpointing potential issues including bugs, security risks, performance constraints, and style violations. AI allows it to review code more efficiently and consistently than a human reviewer could, and on a vastly larger scale. It provides practical recommendations, explanations, and code examples to help rectify the identified problems.
Kilo Code Reviewer scans new pull requests on platforms like GitHub or GitLab automatically. Once a pull request is submitted, the tool assesses the associated changes for potential issues like bugs, security threats, bandwidth problems, or style infringements according to user-specific settings. The tool returns feedback in the form of inline comments on the pull request, providing specific recommendations, explanations, and code examples.
Yes, Kilo Code Reviewer is designed to detect bugs before they reach the code repository. The tool analyzes new code for potential issues, which includes bugs, security risks, performance hurdles, and style breaches. The AI-powered system aids in identifying these issues prior to merging code, thus increasing the overall code quality, boosting productivity, and reducing the potential for problems after merging.
Kilo Code Reviewer provides comprehensive and actionable feedback. It offers comment-based suggestions, backed by explanations and real-world code examples to help rectify identified issues. The feedback is tailored specifically to the issues found in your code. This proactive nature of feedback aids in uncovering and fixing possible problems before the code undergoes a human review.
In Kilo Code Reviewer, users can adjust the settings to focus on specific areas they're interested in. By setting your review style and focus, you have the ability to specify considerations like security, performance, bugs, code style, test coverage, and documentation. These settings can be easily adjusted according to your project requirements and coding standards, giving you a customized review experience.
Kilo Code Reviewer allows users to perform local code reviews within their own Integrated Development Environment (IDE). This feature provides developers realtime feedback on uncommitted changes. Developers can run a local code review directly in their IDE, such as VS Code or JetBrains, get instantaneous feedback on their uncommitted modifications, and catch any potential issues before they are integrated into the repository.
Key benefits of using the Kilo Code Reviewer include automatic code review to identify potential issues before they reach production, enforcing coding standards consistently across the project, learning from review suggestions to improve coding skills, and complementing human code review to ensure best practices are followed.
Yes, Kilo Code Reviewer checks for potential security vulnerabilities in the code. As a part of its review process, it scans through code pertaining to new pull requests, identifying any potential security threats based on the user's predefined settings.
Kilo Code Reviewer aids in the performance optimization of code by identifying areas that can cause performance issues. Based on user-defined settings, the tool scans newly submitted pull requests and examines the related code changes for any performance glitches or bandwidth problems. By flagging these issues, it enables developers to address such concerns before the code undergoes further reviews.
Yes, Kilo Code Reviewer can analyze test coverage. During its review, it focuses on various areas specified by the user, which might include test coverage. By performing a comprehensive examination of the code, Kilo Code Reviewer can point out areas where test coverage might be inadequate, facilitating a more thorough testing process to ensure optimum code performance.
Kilo Code Reviewer features a documentation review option that can be controlled through the user-defined settings. The AI is able to scrutinize the code documentation for any potential issues, irregularities, or areas of improvement. This reinforces the overall comprehensibility, readability, and maintainability of the codebase.
The Kilo Code Reviewer is compatible with several popular coding platforms like GitHub and GitLab. This ensures seamless integration and secure operations across multiple platforms, thereby providing developers with a flexible and adaptable environment for code reviews.
Setting up Kilo Code Reviewer is fairly straightforward. The setup process includes connecting the GitHub or GitLab, choosing the preferred AI model, specifying the review style and focus, and adding any custom instructions. The tool offers clear instructions each step of the way, making it easier to onboard for users unfamiliar with tools of this nature.
Kilo Code Reviewer offers a multitude of different AI models that users can select for code analysis based on their requirements and the nature of the code under review. The website mentions state-of-the-art models like Claude 4 Opus for deeper inspection, or more cost-effective alternatives like Gemini 2.5 Pro for routine reviews.
Yes, the personalized review style and focus in Kilo Code Reviewer allows users to guide the AI's analysis towards specific considerations. This means the tool offers different settings to manage how rigorous the reviews should be (strict, balanced, or lenient) and what to concentrate on, such as security, performance, bugs, code style, test coverage, or documentation.
Kilo Code Reviewer ensures the protection and security of your codebase by implementing read-only access. This means the tool can read and review your code without making any changes, guaranteeing the undiluted integrity of your original code. It is compatible with secure platforms like GitHub and GitLab, which have their own extensive security measures, thereby providing an extra layer of protection.
Kilo Code Reviewer has a local code review feature, which lets developers evaluate their code directly within their own Integrated Development Environment (IDE) before checking it in. This real-time, local feedback enables potential bugs, security vulnerabilities and code quality issues to be identified and resolved before they ever reach the repository.
Based on the content from their website, Kilo Code Reviewer provides certain models for free. It is now free with GLM-4.7 and MiniMax M2.1 models, offering unlimited AI-powered code reviews at no cost. However, the website does not provide exhaustive details about other pricing options, if any.
Yes, Kilo Code Reviewer can be used for team collaboration and codebase management. The tool's adaptive framework facilitates team-wide consistency and understanding with integrated feedback and alert systems. It ensures consistent code practices across the team, comprehensively tracks revisions, and contributes to the overall project management.
Yes, Kilo Code Reviewer allows users to input custom instructions. Users can tell the AI about their coding standards, architectural patterns, or specific things to watch for. The AI is designed to learn and adapt to team's preferences over time.
Yes, Kilo Code Reviewer supports local code reviews. It can review changes locally in user's Integrated Development Environment (IDE) even before the code is committed. It thus provides instant feedback on uncommitted changes, enabling catching of issues before the code reaches the repository.
Kilo Code Reviewer mitigates potential post-merge issues by identifying and rectifying coding issues before they reach the code repository. By offering real-time feedback on pull requests and even uncommitted changes, it allows developers to address these issues early in the development cycle. This reduces the chances of any post-merge issues.
Yes, Kilo Code Reviewer is available for free with certain AI models, such as the MiniMax M2.1 or the GLM 4.7 models. It allows unlimited AI-powered code reviews when these models are used.
Kilo Code Reviewer allows users to choose from a variety of AI models for code analysis. These include state-of-the-art models like Claude 4 Opus for a deeper analysis and cost-effective options like Gemini 2.5 Pro for routine reviews.
Yes, users can set the focus and style of their code reviews with Kilo Code Reviewer. They can adjust how thorough the reviews should be (strict, balanced, or lenient), and choose what to emphasize (security, performance, bugs, code style, test coverage, or documentation).
Yes, Kilo Code Reviewer automatically detects and reviews new pull requests. The system scrutinizes changes in these requests and provides actionable feedback to help rectify detected issues.
Yes, Kilo Code Reviewer can catch bugs before the code reaches the repository. It offers real-time feedback on uncommitted changes in the user's IDE, thus enabling potential bugs, security vulnerabilities, and code quality issues to be addressed early in the development process.
Kilo Code Reviewer integrates seamlessly with a user's Integrated Development Environment (IDE). It allows local code reviews within the IDE, providing real-time feedback on uncommitted changes. This review can be run directly in VS Code or JetBrains giving instant feedback without leaving the editor.
Kilo Code Reviewer is highly adaptable and can integrate with several popular coding platforms. Specific platforms include GitHub and GitLab, with Bitbucket integration also in the pipeline.
The real-time feedback from Kilo Code Reviewer is provided in the form of inline comments on pull requests. It gives specific suggestions, explanations, and code examples to address any issues discovered in the code. This gives developers an opportunity to learn from these comments and implement necessary changes before the code undergoes a human review.
Kilo Code Reviewer increases developer productivity by streamlining the code review process. By catching bugs and other issues early in the development cycle, it reduces the time wasted in fixing post-merge problems. It also enforces coding standards consistently and provides learning opportunities from review suggestions which leads to continual improvement in coding standards and thus productivity.
Kilo Code Reviewer's code reviews are AI-powered as they utilize cutting-edge AI models to analyze the code. This AI technology can review code at a deeper level, recognize and learn coding patterns, monitor user-defined focus areas such as security or performance, and adapt to a team's preferences over time. Furthermore, it can detect bugs, security threats, performance issues, as well as style violations, providing instructive feedback to assist in their rectification.
Kilo Code Reviewer supports different review styles by allowing users to customise the level of thoroughness in their reviews. The review style can be set to strict, balanced, or lenient. The tool also allows users to direct the AI's focus towards specific areas they are interested in such as security, performance, bugs, code style, test coverage, or documentation.
Kilo Code Reviewer is an AI-based tool that provides automated reviews and analyses of code. It inspects pull requests automatically, offering complete feedback derived from the evaluated code. The tool checks for possible problems such as bugs, security risks, performance issues, and style infringements according to user's specified settings. It allows developers to make improvements before the code undergoes a human review. Kilo Code Reviewer supports comment-based recommendations, elucidations, and code examples to aid in rectifying problems. The tool is flexibly designed for easy setup, allowing users to link with platforms like GitHub or GitLab, select appropriate AI models for analysis, set the review style and focus, and provide custom instructions for code inspection.
Kilo Code Reviewer benefits from artificial intelligence to automatically inspect new pull requests and deliver detailed feedback derived from code analysis. By using AI, the tool provides thorough, accurate and instant feedback, pinpointing potential issues including bugs, security risks, performance constraints, and style violations. AI allows it to review code more efficiently and consistently than a human reviewer could, and on a vastly larger scale. It provides practical recommendations, explanations, and code examples to help rectify the identified problems.
Kilo Code Reviewer scans new pull requests on platforms like GitHub or GitLab automatically. Once a pull request is submitted, the tool assesses the associated changes for potential issues like bugs, security threats, bandwidth problems, or style infringements according to user-specific settings. The tool returns feedback in the form of inline comments on the pull request, providing specific recommendations, explanations, and code examples.
Yes, Kilo Code Reviewer is designed to detect bugs before they reach the code repository. The tool analyzes new code for potential issues, which includes bugs, security risks, performance hurdles, and style breaches. The AI-powered system aids in identifying these issues prior to merging code, thus increasing the overall code quality, boosting productivity, and reducing the potential for problems after merging.
Kilo Code Reviewer provides comprehensive and actionable feedback. It offers comment-based suggestions, backed by explanations and real-world code examples to help rectify identified issues. The feedback is tailored specifically to the issues found in your code. This proactive nature of feedback aids in uncovering and fixing possible problems before the code undergoes a human review.
In Kilo Code Reviewer, users can adjust the settings to focus on specific areas they're interested in. By setting your review style and focus, you have the ability to specify considerations like security, performance, bugs, code style, test coverage, and documentation. These settings can be easily adjusted according to your project requirements and coding standards, giving you a customized review experience.
Kilo Code Reviewer allows users to perform local code reviews within their own Integrated Development Environment (IDE). This feature provides developers realtime feedback on uncommitted changes. Developers can run a local code review directly in their IDE, such as VS Code or JetBrains, get instantaneous feedback on their uncommitted modifications, and catch any potential issues before they are integrated into the repository.
Key benefits of using the Kilo Code Reviewer include automatic code review to identify potential issues before they reach production, enforcing coding standards consistently across the project, learning from review suggestions to improve coding skills, and complementing human code review to ensure best practices are followed.
Yes, Kilo Code Reviewer checks for potential security vulnerabilities in the code. As a part of its review process, it scans through code pertaining to new pull requests, identifying any potential security threats based on the user's predefined settings.
Kilo Code Reviewer aids in the performance optimization of code by identifying areas that can cause performance issues. Based on user-defined settings, the tool scans newly submitted pull requests and examines the related code changes for any performance glitches or bandwidth problems. By flagging these issues, it enables developers to address such concerns before the code undergoes further reviews.
Yes, Kilo Code Reviewer can analyze test coverage. During its review, it focuses on various areas specified by the user, which might include test coverage. By performing a comprehensive examination of the code, Kilo Code Reviewer can point out areas where test coverage might be inadequate, facilitating a more thorough testing process to ensure optimum code performance.
Kilo Code Reviewer features a documentation review option that can be controlled through the user-defined settings. The AI is able to scrutinize the code documentation for any potential issues, irregularities, or areas of improvement. This reinforces the overall comprehensibility, readability, and maintainability of the codebase.
The Kilo Code Reviewer is compatible with several popular coding platforms like GitHub and GitLab. This ensures seamless integration and secure operations across multiple platforms, thereby providing developers with a flexible and adaptable environment for code reviews.
Setting up Kilo Code Reviewer is fairly straightforward. The setup process includes connecting the GitHub or GitLab, choosing the preferred AI model, specifying the review style and focus, and adding any custom instructions. The tool offers clear instructions each step of the way, making it easier to onboard for users unfamiliar with tools of this nature.
Kilo Code Reviewer offers a multitude of different AI models that users can select for code analysis based on their requirements and the nature of the code under review. The website mentions state-of-the-art models like Claude 4 Opus for deeper inspection, or more cost-effective alternatives like Gemini 2.5 Pro for routine reviews.
Yes, the personalized review style and focus in Kilo Code Reviewer allows users to guide the AI's analysis towards specific considerations. This means the tool offers different settings to manage how rigorous the reviews should be (strict, balanced, or lenient) and what to concentrate on, such as security, performance, bugs, code style, test coverage, or documentation.
Kilo Code Reviewer ensures the protection and security of your codebase by implementing read-only access. This means the tool can read and review your code without making any changes, guaranteeing the undiluted integrity of your original code. It is compatible with secure platforms like GitHub and GitLab, which have their own extensive security measures, thereby providing an extra layer of protection.
Kilo Code Reviewer has a local code review feature, which lets developers evaluate their code directly within their own Integrated Development Environment (IDE) before checking it in. This real-time, local feedback enables potential bugs, security vulnerabilities and code quality issues to be identified and resolved before they ever reach the repository.
Based on the content from their website, Kilo Code Reviewer provides certain models for free. It is now free with GLM-4.7 and MiniMax M2.1 models, offering unlimited AI-powered code reviews at no cost. However, the website does not provide exhaustive details about other pricing options, if any.
Yes, Kilo Code Reviewer can be used for team collaboration and codebase management. The tool's adaptive framework facilitates team-wide consistency and understanding with integrated feedback and alert systems. It ensures consistent code practices across the team, comprehensively tracks revisions, and contributes to the overall project management.
Pricing
Pricing model
Freemium
Paid options from
$15/month
Billing frequency
Monthly
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