caveman-review

Generate concise code review comments with severity labels for pull requests.

Updated May 6, 2026

Search Tags:#static analysis #code review #pull request #comments #review automation #comments generation

Ready to run

npx skills add https://github.com/wilfoz/plan_game --skill caveman-review-wilfoz

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: caveman-review
Source: https://github.com/wilfoz/plan_game/tree/main/.claude/skills/caveman-review
Command: npx skills add https://github.com/wilfoz/plan_game --skill caveman-review-wilfoz

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the code review process by generating concise, actionable comments, reducing review time and improving feedback quality.

Core Features & Use Cases

Automated Code Review Comments: Produces one-line review comments indicating location, problem, and fix.
Rule-Based Severity Labels: Classifies issues with severity prefixes such as bug, risk, nit, or question.
Use Case: When reviewing a pull request, generate clear, targeted comments on code quality and potential issues to facilitate faster approvals.

Quick Start

Use this Skill to generate code review comments for the provided diff or code snippets.

Frequently Asked Questions about caveman-review

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

FAQPage Schema

How do I generate automated code review comments for a pull request?▼

Automated code review comments are generated by applying rule-based static analysis to your provided diff or code snippets. The skill outputs concise, one-line feedback indicating the location, problem, and fix to streamline pull request approvals.

What is the best way to get concise code review feedback on a code snippet?▼

Concise code review feedback is produced by analyzing code snippets against rule-based severity labels. It generates terse, actionable one-line comments that classify issues as bugs, risks, nits, or questions to improve code quality.

Can I use rule-based static analysis for code review regardless of programming language?▼

Rule-based static analysis for code review can be applied regardless of programming language or project scope. The mechanism generates targeted, actionable comments on code quality and potential issues across different development workflows.

How do automated code review comments classify code issues?▼

Automated code review comments classify code issues using severity prefixes such as bug, risk, nit, or question. This rule-based labeling helps developers quickly identify the urgency and type of problems found during pull request reviews.

Does review automation work for large project scopes and different development workflows?▼

Review automation works for large project scopes and various development workflows by providing language-agnostic, rule-based static analysis. It consistently generates terse, actionable feedback to enhance review clarity regardless of project size.