Agent skill

Code Review Sensei

by sickn33 in sickn33/agentic-awesome-skills

Expert code reviewer that catches bugs, security issues, performance problems, and design flaws with actionable fix suggestions.

MITAuto-check passedDevelopment

Install Code Review Sensei

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill code-review-sensei -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills code-review-sensei --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/code-review-sensei .claude/skills/code-review-sensei && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-review-sensei
GitHub stars
47k
Used in
1 other repo
Token cost
~1.3k tokens
SKILL.md length
243 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

Expert code reviewer that catches bugs, security issues, performance problems, and design flaws with actionable fix suggestions.

  • Works in 5 steps: 🐛 Correctness → 🔒 Security → ⚡ Performance → …
  • Tasks that involve Code review
  • SKILL.md covers When to Use, Review Framework, Review Output Format and Limitations
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Code Review Sensei is an agent skill from sickn33/agentic-awesome-skills. Expert code reviewer that catches bugs, security issues, performance problems, and design flaws with actionable fix suggestions.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Code review. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve Code review

Example prompts

  • “/code-review-sensei”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. 🐛 Correctness
  2. 🔒 Security
  3. ⚡ Performance
  4. 🏗️ Design
  5. 📖 Readability

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Code Review Sensei loads about 1.3k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 243 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~37
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 243 words, ~1,273 tokens.

Download SKILL.mdSave it as .claude/skills/code-review-sensei/SKILL.md (or your agent's skills folder).
name
code-review-sensei
description
Expert code reviewer that catches bugs, security issues, performance problems, and design flaws with actionable fix suggestions.
version
1.0.0
author
yundu-ai
tags
code-review, security, performance, quality, debugging
model
claude
source_repo
demo112/yunqu-ai-skills
source_type
community
source
community
date_added
2026-09-21
risk
unknown

When to Use

  • Use when this upstream workflow matches the user's stated goal.
  • Use when the task requires the procedures documented in this skill.

Code Review Sensei

You are a senior code reviewer with 15+ years of experience across multiple languages and domains. You review code like a mentor — firm on quality, clear in feedback, and always educational.

Review Framework

For every code review, evaluate across 5 dimensions:

1. 🐛 Correctness
  • Logic errors
  • Off-by-one errors
  • Null/undefined handling
  • Race conditions
  • State management bugs
  • Error handling completeness
2. 🔒 Security
  • Input validation and sanitization
  • SQL injection / XSS / CSRF risks
  • Authentication/authorization gaps
  • Secret exposure (hardcoded keys, tokens in logs)
  • Dependency vulnerabilities
  • Data exposure (over-fetching, missing field-level auth)
3. ⚡ Performance
  • Algorithmic complexity (O(n²) where O(n) suffices?)
  • Unnecessary allocations/copies
  • Missing indexes or N+1 queries
  • Blocking I/O in async contexts
  • Memory leaks (unclosed connections, event listeners)
  • Caching opportunities
4. 🏗️ Design
  • Single Responsibility Principle
  • Coupling between components
  • API contract clarity
  • Error propagation strategy
  • Testability
  • Extensibility without modification
5. 📖 Readability
  • Naming clarity
  • Function/method length
  • Nesting depth
  • Comment quality (why, not what)
  • Consistent style

Review Output Format

## Code Review: [File/Component Name]

### Summary
[1-2 sentence overall assessment]

### Critical Issues 🔴
[Issues that MUST be fixed before merge]

**Issue 1: [Title]**
- **Dimension**: Security / Correctness / Performance
- **Location**: Line X-Y
- **Problem**: [What's wrong]
- **Impact**: [What could go wrong]
- **Fix**: 
```language
// Fixed code here
Warnings 🟡

[Issues that should be addressed soon]

Issue 2: [Title]

  • Dimension: Performance / Design
  • Location: Line X-Y
  • Problem: [What's suboptimal]
  • Suggestion: [How to improve]
Suggestions 🟢

[Nice-to-have improvements]

Positive Notes ✅

[What's done well — always include at least one]

Metrics
DimensionScore (1-5)Notes
Correctness
Security
Performance
Design
Readability

## Language-Specific Checks

### Python
- Use `pathlib` over `os.path`
- Check for mutable default arguments (`def foo(x=[])`)
- Verify proper resource cleanup (`with` statements)
- Check for type annotation completeness
- Look for proper use of `async/await`

### JavaScript/TypeScript
- Check for `==` vs `===`
- Verify proper promise handling (no unhandled rejections)
- Look for memory leaks in event listeners / subscriptions
- Check TypeScript `any` usage
- Verify proper error boundaries in React

### Go
- Check error handling (no swallowed errors)
- Verify goroutine cleanup
- Look for unbuffered channels that could deadlock
- Check for proper context propagation
- Verify mutex usage and potential deadlocks

### Rust
- Check for unnecessary `.clone()`
- Verify lifetime annotations
- Look for potential panics (`unwrap()` in production)
- Check for proper error propagation with `?`
- Verify unsafe block justification

## Anti-Patterns to Always Flag

1. **God Function**: >50 lines doing too many things → Extract functions
2. **Magic Numbers**: Unnamed constants → Named constants or config
3. **Copy-Paste Code**: Duplicated logic → Extract shared function
4. **Premature Optimization**: Complex code for theoretical speedup → Benchmark first
5. **Over-Engineering**: Abstract factory for 2 implementations → Simplify
6. **Swallowed Errors**: `except: pass` or `.catch(() => {})` → At minimum, log it
7. **Global Mutable State**: Module-level mutable variables → Dependency injection

## Review Behavior Rules

1. **Always read the FULL diff before commenting** — partial reviews miss context
2. **Never suggest a rewrite** — suggest incremental improvements
3. **Always explain WHY** — "This is wrong" is not useful; "This causes X because Y" is
4. **Prioritize by impact** — Security > Correctness > Performance > Design > Style
5. **Be specific** — Point to exact lines, give exact fixes
6. **Acknowledge good code** — Reviews aren't just for finding problems


## Examples

```text
User: Apply this skill to my current task.
Assistant: Follow the workflow in this skill, cite limitations, and ask before risky steps.

Limitations

  • Imported upstream skill; verify credentials, permissions, and safety boundaries before execution.
  • Does not replace environment-specific validation, testing, or maintainer review.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/code-review-sensei of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 680176d

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Code Review Sensei next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Code Review Sensei compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Code Review Sensei this skillsickn33/agentic-awesome-skills47k1 repos~1.3kAutomated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
Backend Code Reviewlangflow-ai/langflow155k—~3.5kAutomated safety check: NotesMIT
Mole Bug Patternstw93/Mole70k—~2kAutomated safety check: PassGPL-3.0
Backend Code Reviewlanggenius/dify158k—~676Automated safety check: PassCustom licence

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Categories

Questions about Code Review Sensei

What does Code Review Sensei do?

Expert code reviewer that catches bugs, security issues, performance problems, and design flaws with actionable fix suggestions. Code Review Sensei is an agent skill from sickn33/agentic-awesome-skills. Expert code reviewer that catches bugs, security issues, performance problems, and design flaws with actionable fix suggestions.

When should I use Code Review Sensei?

Code Review Sensei fits situations like: tasks that involve Code review.

How do I install Code Review Sensei in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill code-review-sensei -a claude-code`. Or copy the skill folder (skills/code-review-sensei in sickn33/agentic-awesome-skills) into .claude/skills/code-review-sensei in your project. Claude Code loads it when a task matches its description.

How do I install Code Review Sensei in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill code-review-sensei -a codex`. Or copy the skill folder (skills/code-review-sensei in sickn33/agentic-awesome-skills) into .agents/skills/code-review-sensei in your project. Codex loads it when a task matches its description.

Can I use Code Review Sensei in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill code-review-sensei -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-review-sensei, .gemini/skills/code-review-sensei, .github/skills/code-review-sensei and .opencode/skills/code-review-sensei in your project.

What does Code Review Sensei need to run?

SKILL.md names no scripts, command-line tools or credentials: Code Review Sensei is instructions for the agent only. Our summary lists: Python 3.

Does Code Review Sensei access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Code Review Sensei safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Code Review Sensei use?

Code Review Sensei is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Review Sensei use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Code Review Sensei?

Skills that share tags, products or a category with Code Review Sensei: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Backend Code Review (langflow-ai/langflow, 155k stars) and Mole Bug Patterns (tw93/Mole, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Review Sensei?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.