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llm-code-review

Review code changes for correctness, tests, documentation, portability, and performance.

4|3|Updated Feb 18, 2026
Search Tags:#code quality#automation#git#developer tools#code review#ai assistant
One-click install
npx skills add https://github.com/Arm-Examples/LLM-Runner --skill llm-code-review
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-code-review
Source: https://github.com/Arm-Examples/LLM-Runner/tree/main/skills/llm-code-review
Command: npx skills add https://github.com/Arm-Examples/LLM-Runner --skill llm-code-review

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of reviewing code changes, providing actionable feedback to improve code quality, correctness, and maintainability.

Core Features & Use Cases

  • Automated Code Analysis: Analyzes code diffs for potential issues across correctness, testing, documentation, portability, and performance.
  • Actionable Comments: Generates review comments formatted for direct use in code review tools.
  • Use Case: When a developer submits a pull request, this Skill can provide an initial round of feedback, highlighting potential bugs or areas for improvement before human reviewers engage.

Quick Start

Use the llm-code-review skill to review the current code changes.

Frequently Asked Questions about llm-code-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate code review for a pull request?▼

To automate code review for a pull request, this Skill analyzes repository code diffs to generate actionable comments on correctness, testing, and documentation before human reviewers engage.

What does automated code analysis check for in a git repository?▼

Automated code analysis in a git repository checks code diffs for potential issues across correctness, testing, documentation, portability, and performance to provide actionable feedback for software development workflows.

Can I use AI to review code changes locally before submitting?▼

You can use AI to review code changes locally by running this Skill within your local git repository context to generate actionable comments on code quality and performance.

Do I need a local git repository to run an AI code review?▼

Yes, you need a local git repository context to run an AI code review, as the Skill requires repository diffs and adherence to repo-specific expectations for build, test, and API changes.

What is the best way to generate actionable comments on code diffs?▼

The best way to generate actionable comments on code diffs is using an AI assistant that analyzes changes for correctness and performance, formatting the output directly for code review tools.

Are there limitations when using an AI assistant for code quality assurance?▼

A limitation of using an AI assistant for code quality assurance is that it requires local git repository context and strict adherence to repo-specific expectations for build, test, and API changes to function accurately.

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