About LaReview
Overview
LaReview is a local-first code review workbench designed for senior engineers who want to understand system impact, not just catch surface bugs. Unlike AI tools that auto-post comment spam, LaReview helps engineers plan their review, map change flows, and produce focused, high-signal feedback.
It works alongside existing AI coding agents — including Claude, Codex, Gemini, and others — rather than replacing them. All data stays local with zero intermediate servers, directly addressing privacy concerns common with cloud-based code review tools.
Key Benefits
- Transforms PRs or diffs into structured review plans grouped by flow and ordered by risk, not raw file order.
- Keeps all data local — fetches GitHub/GitLab data via the CLI with no intermediate servers involved.
- Learns from rejected feedback by analyzing "ignored" suggestions to reduce nitpicks and improve future review signal.
- Automatically generates architectural diagrams before you read a single line of code.
- Supports custom rules such as "DB queries must have timeouts" to enforce team standards automatically.
- Submits review feedback directly to GitHub or GitLab PRs with auto-generated summaries.
How It Works
You paste a unified diff or a GitHub/GitLab PR URL into LaReview, which then fetches data locally via the GitHub or GitLab CLI. Your chosen AI coding agent analyzes the change and builds a task tree grouped by flow and risk. You execute the plan, add notes, track status, and push the completed review directly to GitHub or GitLab with an auto-generated summary.
Use Cases
- Senior software engineers who need to understand architectural impact of a change before writing any comments.
- Staff engineers conducting structured PR reviews who want risk-ordered tasks rather than file-by-file scanning.
- Engineering teams with strict coding standards who use custom rules to automatically flag violations like missing DB timeouts or missing migration notes.
- Security-conscious developers who require that no code or diff data leaves their local machine during review.
- CLI-first developers who want to launch reviews directly from the terminal by piping git diff output.
- Teams already using AI coding agents such as Claude Code or Codex who want a review layer on top of their existing workflow.
Why Choose This Product
LaReview is best suited for senior engineers and engineering teams who prioritize review depth and data privacy over speed and convenience. It is free and open source under MIT/Apache 2.0 licenses, making it accessible without vendor lock-in.
Key Features
AI-Powered Planning
LaReview accepts a PR URL or diff and acts as a staff engineer to build a structured, flow-based review plan that identifies hazards.
Task-Focused Review
Review tasks are grouped by flow and ordered by risk, with a files heatmap to track progress and navigate the change.
High-Signal Feedback
The AI proactively identifies bugs and validates them against user-defined rules, producing focused feedback threads anchored to specific code lines.
Custom Rules
Users define rules such as "DB queries must have timeouts" or "API changes need a migration note" to automatically enforce team standards.
Local Context Linking
Users link local Git repos to give the agent full codebase search access without uploading any files to external servers.
Git Host Sync
LaReview submits completed review feedback directly to GitHub or GitLab PRs with automatic summary generation.
Visual Diagrams
LaReview automatically generates architectural diagrams of the change before the user reads any code.
Learning Patterns
The AI learns from suggestions marked as "ignored" and analyzes rejection patterns to calibrate and reduce nitpicks in future reviews.
CLI Support
Reviews can be launched directly from the terminal by running `lareview`, specifying a PR, or piping a git diff to the `lareview` command.
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