GitLab MR Review for Openclaw

An automated code review utility that analyzes GitLab merge requests and posts standardized feedback via CLI integration.

wujinyuan
v1.0.0
Mar 17, 2026
0
946
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install gitlab-mr-review

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install gitlab-mr-review using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is GitLab MR Review?

The GitLab MR Review skill is a powerful extension designed to automate the manual toil of code reviews. By integrating directly with the GitLab API via the glab CLI, it allows AI agents to parse merge request URLs, analyze diffs, and generate high-quality feedback based on a standardized template. This ensures that every code submission is checked for common pitfalls, security risks, and style consistency before a human reviewer even opens the page.

Using this skill within the ecosystem of Openclaw Skills enables teams to maintain high code quality standards while significantly reducing the time spent on initial review cycles. It bridges the gap between raw code changes and actionable developer feedback by providing structured summaries and specific improvement suggestions directly in the GitLab UI.

GitLab MR Review Use Cases

  • Automatically reviewing incoming merge requests to identify TODOs, hardcoded values, or missing error handling.
  • Enforcing a consistent code review format across multiple repositories and teams.
  • Providing instant, first-pass feedback to developers in asynchronous or remote environments using Openclaw Skills.
  • Reducing the workload of senior developers by filtering out basic syntax or style issues automatically.

How GitLab MR Review Works

  1. The agent parses the provided GitLab MR URL to extract the hostname, project path, and merge request IID.
  2. It configures the glab CLI to point to the correct GitLab instance for authenticated access.
  3. The skill calls the GitLab API to fetch the merge request metadata and the complete diff of changes.
  4. It analyzes the code changes against a provided Markdown template, scanning for bugs, security vulnerabilities, and style issues.
  5. A structured review comment is generated, categorizing feedback into overview, strengths, suggestions, and critical issues.
  6. The final analysis is posted back to the GitLab merge request as a formal note or comment.

GitLab MR Review Setup

To use this skill, ensure the glab CLI is installed on your system. You must also have a valid GitLab personal access token configured.

# Configure the GitLab host
glab config set host https://your-gitlab-instance.com

# Ensure you have a template file named code-review-template.md in your path

The AI agent will use the glab API to interact with your projects, so ensure it has the necessary permissions to read and post comments to merge requests.

GitLab MR Review Data Schema & Taxonomy

The skill organizes its analysis using the following data structures:

Attribute Description
MR Metadata Extracted from URL: Host, Project Path, and IID.
API Response JSON data containing MR status and code diffs from GitLab.
Review Template A Markdown-based schema (code-review-template.md) defining the output structure.
Final Comment A generated Markdown file containing the summary, suggestions, and checklist for the developer.

GitLab MR Review Advanced Features

  • Support for custom self-hosted GitLab instances and private enterprise environments.
  • Automatic severity highlighting using emojis to distinguish between critical bugs and minor warnings.
  • Integration with Openclaw Skills to provide context-aware suggestions based on project-specific guidelines.
  • Ability to post line-specific feedback by referencing file paths and line numbers in the generated report.

SKILL.md


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