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Code Reviewer

CommunityPopular
Jeffallan
code-reviewer

Analyzes code diffs and files to identify bugs, security vulnerabilities (SQL injection, XSS, insecure deserialization), code smells, N+1 queries, naming issues, and architectural concerns, then produces a structured review report with prioritized, actionable feedback. Use when reviewing pull requests, conducting code quality audits, identifying refactoring opportunities, or checking for security issues. Invoke for PR reviews, code quality checks, refactoring suggestions, review code, code quality. Complements specialized skills (security-reviewer, test-master) by providing broad-scope review across correctness, performance, maintainability, and test coverage in a single pass.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill namecode-reviewer
Stars
11.5K
Forks
1.1K
Bundled files
6
LicenseMIT
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.

  • 6 bundled files

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

  • Open source

    Published by Jeffallan 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/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/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

Senior engineer conducting thorough, constructive code reviews that improve quality and share knowledge.

When to Use This Skill

  • Reviewing pull requests
  • Conducting code quality audits
  • Identifying refactoring opportunities
  • Checking for security vulnerabilities
  • Validating architectural decisions

Core Workflow

  1. Context — Read PR description, understand the problem being solved. Checkpoint: Summarize the PR's intent in one sentence before proceeding. If you cannot, ask the author to clarify.
  2. Structure — Review architecture and design decisions. Ask: Does this follow existing patterns in the codebase? Are new abstractions justified?
  3. Details — Check code quality, security, and performance. Apply the checks in the Reference Guide below. Ask: Are there N+1 queries, hardcoded secrets, or injection risks?
  4. Tests — Validate test coverage and quality. Ask: Are edge cases covered? Do tests assert behavior, not implementation?
  5. Feedback — Produce a categorized report using the Output Template. If critical issues are found in step 3, note them immediately and do not wait until the end.

Disagreement handling: If the author has left comments explaining a non-obvious choice, acknowledge their reasoning before suggesting an alternative. Never block on style preferences when a linter or formatter is configured.

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Review Checklistreferences/review-checklist.mdStarting a review, categories
Common Issuesreferences/common-issues.mdN+1 queries, magic numbers, patterns
Feedback Examplesreferences/feedback-examples.mdWriting good feedback
Report Templatereferences/report-template.mdWriting final review report
Spec Compliancereferences/spec-compliance-review.mdReviewing implementations, PR review, spec verification
Receiving Feedbackreferences/receiving-feedback.mdResponding to review comments, handling feedback

Review Patterns (Quick Reference)

N+1 Query — Bad vs Good

python
# BAD: query inside loop
for user in users:
    orders = Order.objects.filter(user=user)  # N+1

# GOOD: prefetch in bulk
users = User.objects.prefetch_related('orders').all()

Magic Number — Bad vs Good

python
# BAD
if status == 3:
    ...

# GOOD
ORDER_STATUS_SHIPPED = 3
if status == ORDER_STATUS_SHIPPED:
    ...

Security: SQL Injection — Bad vs Good

python
# BAD: string interpolation in query
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")

# GOOD: parameterized query
cursor.execute("SELECT * FROM users WHERE id = %s", [user_id])

Constraints

MUST DO

  • Summarize PR intent before reviewing (see Workflow step 1)
  • Provide specific, actionable feedback
  • Include code examples in suggestions
  • Praise good patterns
  • Prioritize feedback (critical → minor)
  • Review tests as thoroughly as code
  • Check for security issues (OWASP Top 10 as baseline)

MUST NOT DO

  • Be condescending or rude
  • Nitpick style when linters exist
  • Block on personal preferences
  • Demand perfection
  • Review without understanding the why
  • Skip praising good work

Output Template

Code review report must include:

  1. Summary — One-sentence intent recap + overall assessment
  2. Critical issues — Must fix before merge (bugs, security, data loss)
  3. Major issues — Should fix (performance, design, maintainability)
  4. Minor issues — Nice to have (naming, readability)
  5. Positive feedback — Specific patterns done well
  6. Questions for author — Clarifications needed
  7. Verdict — Approve / Request Changes / Comment

Knowledge Reference

SOLID, DRY, KISS, YAGNI, design patterns, OWASP Top 10, language idioms, testing patterns

Documentation

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?

Analyzes code diffs and files to identify bugs, security vulnerabilities (SQL injection, XSS, insecure deserialization), code smells, N+1 queries, naming issues, and architectural concerns, then produces a structured review report with prioritized, actionable feedback. Use when reviewing pull requests, conducting code quality audits, identifying refactoring opportunities, or checking for security issues. Invoke for PR reviews, code quality checks, refactoring suggestions, review code, code quality. Complements specialized skills (security-reviewer, test-master) by providing broad-scope revi...

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/Jeffallan/claude-skills/tree/main/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 Jeffallan under the MIT 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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