code-review

Analyzes code diffs and generates a structured review with severity ratings.

Updated Apr 23, 2026
One-click install
npx skills add https://github.com/wmasfoe/notch-pet --skill code-review-wmasfoe
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: code-review
Source: https://github.com/wmasfoe/notch-pet/tree/main/.codex/skills/code-review
Command: npx skills add https://github.com/wmasfoe/notch-pet --skill code-review-wmasfoe

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides structured, objective code reviews across changes to improve quality, security, and maintainability.

Core Features & Use Cases

  • Automated diff analysis: identifies changes, potential security vulnerabilities, and maintainability concerns.
  • Dual-lane guidance: delegates to the code-reviewer and architect lanes in parallel, then synthesizes findings for a merge decision.
  • Before-merge gating & actionable output: produces severity-weighted findings and concrete remediation steps.

Quick Start

Request a code review for the latest changes and receive a structured report with severity ratings and concrete remediation steps.

Frequently Asked Questions about code-review

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

FAQPage Schema
How do I automate code reviews for pull requests to improve maintainability?

Automated code review analyzes pull request diffs to identify changes, assess quality, and generate a structured report with severity ratings and actionable remediation steps to improve maintainability.

What is the best way to assess security vulnerabilities in a code diff before merging?

Assessing security vulnerabilities in a code diff before merging involves identifying changes, evaluating security implications, and producing severity-weighted findings with concrete code edits to gate merges.

Can I use review automation across different programming languages and frameworks?

Yes, review automation applies to pull requests or code diffs across languages and frameworks, evaluating security implications and maintainability concerns to ensure a deterministic final merge decision.

How does dual-lane guidance work for generating a structured code review?

Dual-lane guidance delegates code changes to the code-reviewer and architect lanes in parallel, then synthesizes findings to produce a deterministic final verdict with actionable recommendations and severity ratings.

What are the limitations of automated code review for software quality?

Automated code review limitations include its reliance on identifying code changes within diffs, meaning it evaluates security and maintainability strictly based on the provided pull request context rather than the entire repository history.