Review

Product Introduction

1. Definition: Review is a free, open-source (MIT licensed) desktop application for conducting secure, offline-first code reviews. It operates as a local Git client and GitHub pull request (PR) reviewer, enabling developers to analyze branches and PRs directly on their machine without exposing draft feedback.
2. Core Value Proposition: It exists to give developers and engineering teams full control, privacy, and flexibility in the code review process. By running locally, it eliminates reliance on cloud-based review tools, ensures comments remain private until explicitly published, and allows the integration of custom AI models (including local LLMs) for automated analysis without sending code to third-party APIs unless configured.

Main Features

1. Local-First, Private Commenting: The app allows reviewers to click on any line number within a diff to add a comment. All draft comments are saved locally to the user's computer in real-time as they type. This data never leaves the machine until the user manually chooses to publish the review to GitHub, addressing concerns about premature feedback or accidental sharing.
2. Bring-Your-Own-Model (BYOM) AI Review: Unlike SaaS tools with locked-in AI, Review supports a wide array of AI backends. Users can configure it to use major commercial APIs (OpenAI GPT, Anthropic Claude, Google Gemini), aggregators (OpenRouter, OmniRoute), or locally-hosted models via Ollama or LM Studio. It can also pull additional context from MCP (Model Context Protocol) servers. This allows teams to use proprietary models, control costs, and ensure code never leaves their infrastructure.
3. Commit-Pinned Diff Analysis & Unified Navigation: Reviews are intelligently pinned to the exact merge base commit between branches. This prevents the diff view from shifting and causing comment misplacement if new commits are pushed during the review. The global command palette (activated by Cmd/Ctrl + P) provides rapid keyboard-driven navigation to pending PRs, recent reviews, and local branches, streamlining workflow.

Problems Solved

1. Pain Point: The risk of accidental early feedback submission in cloud-based PR interfaces and the lack of privacy during the draft review phase. It also solves the inflexibility of built-in AI code review tools that mandate using a specific vendor's model and sending code to external servers.
2. Target Audience: Software developers, engineering team leads, and open-source maintainers who prioritize code privacy, especially those in regulated industries or working with proprietary codebases. It's also ideal for AI enthusiasts and teams who have invested in fine-tuned or local LLMs and want to leverage them for code analysis.
3. Use Cases: Conducting sensitive security reviews on proprietary algorithms; providing detailed, draft feedback on a complex PR over multiple sessions without notifying the author prematurely; using a company's privately-hosted LLM (via Ollama) to run standard compliance checks; quickly reviewing a batch of PRs offline while traveling.

Unique Advantages

1. Strengths & Limitations (Pros & Cons):
   • Pros: Unmatched privacy and data control; exceptional flexibility in AI model choice; open-source transparency and self-hosting potential; free to use; lightweight desktop-centric workflow; avoids "notification noise" for PR authors.
   • Cons: Requires manual installation and potential security approval for unsigned binaries; dependent on local Git installation; lacks real-time collaborative editing features found in web-based tools; AI setup requires user configuration, which has a learning curve.
2. Key Alternatives & Differentiation:
   • GitHub/GitLab Native Interface: The primary alternative. Review differentiates by providing offline work, draft privacy, and customizable AI. Native platforms offer seamless integration and collaboration but lack local AI options and keep all draft comments on their servers.
   • PullRequest.com / CodeStream (SaaS AI Review): These are cloud-based services that integrate AI review. Review differentiates by being a free, offline desktop app that doesn't route code through a third-party's AI unless you explicitly choose to. It puts the user in complete control of the AI model and data pipeline.
   • Other Local Git GUIs (Fork, GitKraken): These clients focus on broader Git operations. Review is specifically hyper-optimized for the code review workflow, with deep PR integration, line commenting, and a dedicated AI review engine, which general Git GUIs lack.

Frequently Asked Questions (FAQ)

1. Is Review really free and private? Yes, Review is completely free, open-source software. All code review comments and draft data are stored locally on your computer. Nothing is sent to any external server unless you manually publish to GitHub or explicitly configure an external AI API.
2. Can I use Review for code review without an AI model? Absolutely. The AI reviewer is an entirely optional feature. The core functionality is a powerful, private desktop client for reviewing Git diffs and GitHub Pull Requests with local commenting.
3. How do I set up a local AI model like Llama 3 with Review? You can use a local inference server like Ollama. After installing Ollama and pulling a model (e.g., ollama pull llama3.2), you simply configure Review to point to your local Ollama endpoint (typically http://localhost:11434). Your code never leaves your machine.
4. What are the system requirements for the Review app? You need to have Git installed on your system. The app itself is available for macOS (Apple Silicon and Intel), Windows 10/11, and Linux (x64 AppImage). It requires Node.js 22.12+ if you choose to build it from source.
5. Why does my operating system show a security warning when installing? Because the application is not currently signed with a paid Apple Developer or Microsoft certificate. This is common for free, open-source software. You can safely bypass this warning by following the instructions on the download page, which involve allowing the app in your system's security settings. The source code is publicly available for audit.