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Code Reviewer

CommunityPopular
foryourhealth111-pixel
code-reviewer

Default code-quality route for broad code review, PR review, maintainability, correctness, and regression-risk checks. Do not use as the primary route for dedicated OWASP/security audits, review-feedback handling, completion verification, AI-code cleanup, or TDD/test-first work.

Overview

Publisherforyourhealth111-pixel
RepositoryVibe-Skills
Skill namecode-reviewer
Stars
3.3K
Forks
288
Bundled files
8
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by foryourhealth111-pixel on GitHub. Read the source before you install it.

Installation

Install the Code Reviewer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills.git /tmp/Vibe-Skills
mkdir -p .claude/skills
cp -r /tmp/Vibe-Skills/bundled/skills/code-reviewer .claude/skills/code-reviewer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Reviewer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Reviewer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Reviewer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Reviewer

Complete toolkit for code reviewer with modern tools and best practices.

Routing Boundary

Use code-reviewer when the user asks for a fresh review of code or a PR:

  • correctness and likely bugs
  • maintainability and readability
  • regression risk
  • test coverage gaps from a reviewer's point of view

Do not let this skill own narrower problems:

  • security-reviewer owns OWASP, secret leak, auth bypass, injection, and dedicated security audit prompts.
  • receiving-code-review owns existing CodeRabbit/GitHub/human review comments.
  • verification-before-completion owns final evidence before claiming work is done.
  • deslop owns cleanup of AI-generated comments, redundant guards, and boilerplate.
  • tdd-guide owns test-first or RED -> GREEN -> REFACTOR development.

Migrated Legacy Assets

The legacy review wrapper has been absorbed into this direct route owner.

  • references/python-style-guide.md contains the retained Python naming, import, documentation, error-handling, and secret-handling guidance.
  • scripts/check_style.py is a lightweight stdin/string style checker for quick local review support.

Use these assets as supporting material inside code-reviewer; do not route to the deleted wrapper skill.

Quick Start

Main Capabilities

This skill provides three core capabilities through automated scripts:

bash
# Script 1: Pr Analyzer
python scripts/pr_analyzer.py [options]

# Script 2: Code Quality Checker
python scripts/code_quality_checker.py [options]

# Script 3: Review Report Generator
python scripts/review_report_generator.py [options]

Core Capabilities

1. Pr Analyzer

Automated tool for pr analyzer tasks.

Features:

  • Automated scaffolding
  • Best practices built-in
  • Configurable templates
  • Quality checks

Usage:

bash
python scripts/pr_analyzer.py <project-path> [options]

2. Code Quality Checker

Comprehensive analysis and optimization tool.

Features:

  • Deep analysis
  • Performance metrics
  • Recommendations
  • Automated fixes

Usage:

bash
python scripts/code_quality_checker.py <target-path> [--verbose]

3. Review Report Generator

Advanced tooling for specialized tasks.

Features:

  • Expert-level automation
  • Custom configurations
  • Integration ready
  • Production-grade output

Usage:

bash
python scripts/review_report_generator.py [arguments] [options]

Reference Documentation

Code Review Checklist

Comprehensive guide available in references/code_review_checklist.md:

  • Detailed patterns and practices
  • Code examples
  • Best practices
  • Anti-patterns to avoid
  • Real-world scenarios

Coding Standards

Complete workflow documentation in references/coding_standards.md:

  • Step-by-step processes
  • Optimization strategies
  • Tool integrations
  • Performance tuning
  • Troubleshooting guide

Common Antipatterns

Technical reference guide in references/common_antipatterns.md:

  • Technology stack details
  • Configuration examples
  • Integration patterns
  • Security considerations
  • Scalability guidelines

Tech Stack

Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin Frontend: React, Next.js, React Native, Flutter Backend: Node.js, Express, GraphQL, REST APIs Database: PostgreSQL, Prisma, NeonDB, Supabase DevOps: Docker, Kubernetes, Terraform, GitHub Actions, CircleCI Cloud: AWS, GCP, Azure

Development Workflow

1. Setup and Configuration

bash
# Install dependencies
npm install
# or
pip install -r requirements.txt

# Configure environment
cp .env.example .env

2. Run Quality Checks

bash
# Use the analyzer script
python scripts/code_quality_checker.py .

# Review recommendations
# Apply fixes

3. Implement Best Practices

Follow the patterns and practices documented in:

  • references/code_review_checklist.md
  • references/coding_standards.md
  • references/common_antipatterns.md

Best Practices Summary

Code Quality

  • Follow established patterns
  • Write comprehensive tests
  • Document decisions
  • Review regularly

Performance

  • Measure before optimizing
  • Use appropriate caching
  • Optimize critical paths
  • Monitor in production

Security

  • Flag obvious security risks during a general review.
  • Route dedicated OWASP, auth, secret, injection, or threat-model requests to security-reviewer.

Maintainability

  • Write clear code
  • Use consistent naming
  • Add helpful comments
  • Keep it simple

Common Commands

bash
# Development
npm run dev
npm run build
npm run test
npm run lint

# Analysis
python scripts/code_quality_checker.py .
python scripts/review_report_generator.py --analyze

# Deployment
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/

Troubleshooting

Common Issues

Check the comprehensive troubleshooting section in references/common_antipatterns.md.

Getting Help

  • Review reference documentation
  • Check script output messages
  • Consult tech stack documentation
  • Review error logs

Resources

  • Pattern Reference: references/code_review_checklist.md
  • Workflow Guide: references/coding_standards.md
  • Technical Guide: references/common_antipatterns.md
  • Tool Scripts: scripts/ directory

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Code Reviewer AI skill do?

Default code-quality route for broad code review, PR review, maintainability, correctness, and regression-risk checks. Do not use as the primary route for dedicated OWASP/security audits, review-feedback handling, completion verification, AI-code cleanup, or TDD/test-first work.

Why use Code Reviewer on TypingMind?

Because you install it once and use it with any model. Code Reviewer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Reviewer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/main/bundled/skills/code-reviewer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Code Reviewer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Reviewer?

As many as you like. As long as a model supports skills, you can use Code Reviewer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Reviewer AI skill free?

Yes. It is published on GitHub by foryourhealth111-pixel under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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