The Code Review Workbench.
[](https://github.com/user-attachments/assets/28abaf1e-9100-4484-b6a5-18d8dfec427e) --- LaReview is a **dev-first code review workbench** for complex changes. It turns a PR or diff into a structured review plan, grouped by flows and ordered by risk, so you can review with depth and understanding. Unlike auto-review bots that post comment spam, LaReview is a local-first tool that works with your existing AI coding agent to help you ship high-signal feedback. ## Example review The feature screenshots follow an illustrative payment-webhook review: six changed files, four tasks, and two blockers. [See the example scenario](docs/SCREENSHOTS.md). ## Key Features LaReview is designed for a local-first, secure, and focused review experience. | Feature | Workflow | | :--- | :--- | | **AI-Powered Planning** | Load a GitHub or GitLab pull request, compare local Git refs, or paste a diff. LaReview acts as a staff engineer, looking for flows (e.g. auth, api) and risks to build a structured review plan. | | **Review Tasks** | Follow the review plan by flow, track progress, and focus on the highest-risk concerns first. | | **Task Analysis** | Work through a focused verification plan for each logical concern. Mark tasks as **To Do**, **In Progress**, or **Done**. Attach contextual notes to specific tasks or lines of code to keep track of your thoughts. | | **Task-Focused Diffs** | Review one logical concern at a time. The workbench isolates relevant code hunks for each task, eliminating noise. | | **High-Signal Framework** | The AI proactively identifies bugs and authenticates them against your rules. No comment spam—just focused feedback threads anchored to specific lines. | | **Local Context** | Link local Git repos to give the agent full access to search your codebase. Works with your existing AI coding agent using context from your local checkout. | | **Visual Diagrams** | Visualize the flow. Automatically generate diagrams to see architectural changes before you read a single line of code. Rendered with Mermaid. | | **Team Rules** | Define rules like "DB queries must have timeouts" or "API changes need a migration note" to enforce standards automatically. | | **Learning Patterns** | The AI learns from rejected feedback. Mark suggestions as "ignored" during reviews, then analyze rejections to discover patterns that calibrate future reviews—fewer nitpicks, more signal. | | **Git Host Sync** | Submit your review feedback directly to GitHub or GitLab PRs with automatic summary generation. | | **Export & Share** | Export your review summary to Markdown with diagrams and code insights. Copy the selected tasks and feedback to your clipboard. | | **CLI Support** | Launch reviews from the terminal: `lareview`, `lareview pr owner/repo#123`, `git diff | lareview`, or `lareview --agent claude`. | ## Inside the workbench ### A focused review plan  ### A finding with its code and evidence  ### The task’s relevant code changes  ## How it works 1. **Input** - Run `lareview` from terminal (opens GUI with current repo linked), or - Paste a unified diff, or - Paste a code review link from GitHub or GitLab, or a PR URL 2. **Fetch (for PRs)** - LaReview fetches the change locally and prepares the review workspace. No intermediate servers. 3. **Generate a review plan** - Starting creates the review immediately and opens its live Activity page while the selected AI agent works in the background. - You can return to Generate and start another review; two generations can run concurrently and additional reviews wait in a visible queue. - When generation finishes, the same review page automatically becomes the full review workbench. 4. **Review** - Review task by task with your AI coding agent. - Ship focused feedback that authors can act on, without comment spam. ## Terminal Workflow LaReview includes a CLI that integrates naturally into your developer workflow: ```bash # Open GUI with current repository linked lareview # Review changes between branches lareview main feature # Pipe a diff directly to the GUI git diff HEAD | lareview # Review a GitHub/GitLab PR lareview pr owner/repo#123 # Specify an agent lareview --agent claude ``` The CLI launches the GUI in the background and passes your diff/repo info seamlessly. ## On-prem and other Git hosts Clone your repository using your usual Git credentials, then link the local folder in **Repositories**. In **Generate Review**, select that repository, choose **Local Git**, enter a base and head branch, tag, or commit, and click **Compare changes**. Inspect the diff, then click **Start Review** with your chosen agent. Comparison uses the two commit snapshots (`git diff BASE HEAD`) already present locally. Fetch remote branches with Git first. LaReview does not change your checkout or staged changes. The review records both resolved commit IDs and can use the head commit through the existing snapshot permission flow. This works with on-prem Git, Bitbucket, Gitea, Azure DevOps, GitHub Enterprise, and repositories without a remote. Host-specific PR metadata, inbox, and posting comments remain available through the GitHub/GitLab integrations. The terminal workflow also works from any local clone: `lareview main feature` or `git diff main feature | lareview`. ## Supported Agents LaReview launches compatible harnesses through commands already available on your `PATH`, or an executable override configured in Settings. It does not provide an in-app harness installer. | Agent | Launch command | | --- | --- | | Claude | `npx -y @agentclientprotocol/claude-agent-acp@0.65.0` | | Codex | `npx -y @agentclientprotocol/codex-acp@1.1.9` | | GitHub Copilot | `copilot --acp --stdio` | | Gemini | `gemini --acp` | | Grok | `grok --no-auto-update agent stdio` | | Kimi | `kimi acp` | | Mistral | `vibe-acp` | | OpenCode | `opencode acp` | | Qwen | `qwen --acp --experimental-skills` | General ACP support is not sufficient: the harness must forward LaReview's client-provided MCP server and call its tools. `pi-acp` is intentionally unsupported because it does not provide that required MCP behavior. ## Requirements - **Rust 1.99.1** (installed automatically by rustup from `rust-toolchain.toml`; MSRV 1.91) - **Node.js 24.22.2** and **pnpm 11.28.9** for frontend development - **GitHub CLI** (optional): - Install: `brew install gh` (or your OS package manager) - Auth: `gh auth login` - **GitLab CLI** (optional): - Install: `brew install glab` (or your OS package manager) - Auth: `glab auth login` - **AI agent** configured on your machine - Learn more: https://agentclientprotocol.com/overview/introduction > [!NOTE] > LaReview does not require a custom LaReview server. Your PR data is fetched locally via `gh` or `glab`, and plan generation runs via your chosen AI agent. ### GitHub Copilot setup Install the [GitHub Copilot CLI](https://docs.github.com/en/copilot/how-tos/set-up/install-copilot-cli) and sign in by running `copilot` and using `/login`. Restart LaReview, then select **GitHub Copilot** in the Agent picker. If the executable is outside your `PATH`, set its path in Settings. LaReview uses Copilot's native [ACP stdio server](https://docs.github.com/en/copilot/reference/copilot-cli-reference/acp-server); no additional adapter or `gh copilot` extension is needed. Models and session options are discovered from the installed CLI, and require an authenticated Copilot account or a configured bring-your-own-key provider. For each review, LaReview supplies its local task server through Copilot's `--additional-mcp-config` launch option, because Copilot's ACP session API accepts only HTTP/SSE MCP entries. This uses the same local stdio task server as the other agents. ## Installation ### Option A: Homebrew (Recommended) Install LaReview via Homebrew with a single command: #### macOS ```bash # First, tap the repository brew tap puemos/tap # Then install brew install --cask lareview ``` #### Linux ```bash brew install puemos/tap/lareview ``` ### Option B: Download a release 1. Go to the [Releases page](https://github.com/puemos/lareview/releases) and download the latest binary for your operating system. 2. Follow the instructions for your OS below. #### macOS 1. Download `LaReview_