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Code Review

Community
coleam00
code_review

Review code for quality, security, and best practices. Use when analyzing code, suggesting improvements, or conducting code reviews.

Overview

Publishercoleam00
Repositorycustom-agent-with-skills
Skill namecode_review
Stars
107
Forks
42
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

    Published by coleam00 on GitHub. Read the source before you install it.

Installation

Install the Code Review 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.
    https://github.com/coleam00/custom-agent-with-skills/tree/main/skills/code_review
  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/coleam00/custom-agent-with-skills.git /tmp/custom-agent-with-skills
mkdir -p .claude/skills
cp -r /tmp/custom-agent-with-skills/skills/code_review .claude/skills/code_review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Review 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 Review 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 Review 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 Review Skill

Provides comprehensive code review capabilities covering quality, security, and best practices analysis.

When to Use

  • User asks you to review their code
  • User wants to improve code quality
  • User asks about security vulnerabilities in code
  • User wants to identify antipatterns or code smells
  • User requests best practices suggestions
  • User wants a general code quality assessment

Available Operations

  1. Analyze Code Structure: Evaluate organization, modularity, and architecture
  2. Check Best Practices: Compare against established coding standards
  3. Security Review: Identify potential security vulnerabilities
  4. Antipattern Detection: Find common code smells and antipatterns
  5. Generate Review Report: Provide structured feedback with recommendations

Multi-Step Review Workflow

When conducting a code review, follow these steps in order:

Step 1: Initial Code Analysis

Read the code thoroughly and identify:

  • Primary purpose and functionality
  • Programming language and frameworks used
  • Overall structure and organization
  • Entry points and main logic flow

Step 2: Best Practices Check

Evaluate the code against best practices. Load the best practices guide for comprehensive checks:

  • references/best_practices.md - Comprehensive coding standards and practices

Key areas to check:

  • Naming conventions (variables, functions, classes)
  • Function design (single responsibility, proper parameters)
  • Error handling patterns
  • Code organization and modularity
  • Documentation and comments

Step 3: Security Review

Check for security vulnerabilities. Load the security checklist for detailed guidance:

  • references/security_checklist.md - Security review checklist based on OWASP guidelines

Key security areas:

  • Input validation and sanitization
  • Authentication and authorization
  • Injection vulnerabilities (SQL, command, etc.)
  • Data exposure and encryption
  • Dependency security

Step 4: Antipattern Detection

Identify code smells and antipatterns. Load the antipatterns guide for reference:

  • references/common_antipatterns.md - Common antipatterns and how to fix them

Common issues to look for:

  • God classes/functions
  • Deep nesting
  • Magic numbers and strings
  • Copy-paste code
  • Resource leaks

Step 5: Generate Review Report

Compile findings into a structured report:

## Code Review Summary

**File/Module**: [name]
**Language**: [language]
**Overall Assessment**: [Excellent/Good/Needs Improvement/Critical Issues]

### Strengths
- [List positive aspects]

### Issues Found

#### Critical (Must Fix)
- [Security vulnerabilities, bugs]

#### Major (Should Fix)
- [Significant antipatterns, bad practices]

#### Minor (Consider Fixing)
- [Style issues, small improvements]

### Recommendations
1. [Specific actionable recommendations]
2. [...]

### Resources Referenced
- [List which reference files were consulted]

Resources

Reference these files for detailed guidance during reviews:

  • references/best_practices.md - Comprehensive coding best practices covering organization, naming, error handling, testing, and documentation
  • references/security_checklist.md - Security review checklist covering OWASP Top 10, input validation, authentication, and common vulnerabilities
  • references/common_antipatterns.md - Guide to detecting and fixing common antipatterns like god classes, spaghetti code, and resource leaks

Examples

Example 1: Quick Review Request

User asks: "Can you review this function?"

Response approach:

  1. Load this skill's full instructions
  2. Analyze the provided code
  3. Check against best practices (load references/best_practices.md if needed)
  4. Identify any obvious security issues
  5. Provide concise feedback with specific recommendations

Example 2: Security-Focused Review

User asks: "Check this code for security vulnerabilities"

Response approach:

  1. Load this skill's full instructions
  2. Load references/security_checklist.md for comprehensive security checks
  3. Systematically check each security category
  4. Provide detailed security findings with severity ratings
  5. Include specific fix recommendations

Example 3: Comprehensive Code Review

User asks: "I need a thorough code review of my authentication module"

Response approach:

  1. Load this skill's full instructions
  2. Follow the complete multi-step workflow
  3. Load all three reference files as needed
  4. Provide comprehensive report covering all aspects
  5. Prioritize recommendations by impact

Notes

  • Always be constructive in feedback - explain why something is an issue and how to fix it
  • Severity ratings: Critical (security/bugs), Major (significant quality issues), Minor (style/polish)
  • Focus on the most impactful issues first
  • Provide specific code examples when suggesting fixes
  • Consider the context - production code needs higher scrutiny than prototypes
  • Reference specific sections of the guide files when making recommendations

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 Review AI skill do?

Review code for quality, security, and best practices. Use when analyzing code, suggesting improvements, or conducting code reviews.

Why use Code Review on TypingMind?

Because you install it once and use it with any model. Code Review 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 Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coleam00/custom-agent-with-skills/tree/main/skills/code_review. 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 Review?

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 Review?

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

Is the Code Review AI skill free?

It is published on GitHub by coleam00. Check the repository for licensing terms. 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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