
code-review
Perform a structured code review of changes, checking for correctness, style, tests, and potential issues.
- Installs
- 213
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/langchain-ai/deepagents --skill code-review- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads code-review automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Code Review Skill
Use this skill after implementing changes to validate your work before delivering.
Review Checklist
1. Correctness
- Changes solve the original issue/task
- No unintended side effects on existing functionality
- Edge cases are handled
- Error handling is appropriate (not excessive)
2. Code Quality
- Code matches existing style and patterns
- No unnecessary complexity or abstraction
- Variable and function names are clear
- No dead code, commented-out code, or TODOs left behind
3. Tests
- New functionality has test coverage
- Existing tests still pass
- Tests cover both happy path and error cases
- Tests are not brittle (don't test implementation details)
4. Safety
- No hardcoded secrets or credentials
- User input is validated at boundaries
- No SQL injection, XSS, or command injection vectors
- File operations use safe paths
Process
- Read each modified file end-to-end (not just the diff)
- Run the test suite:
execute("python -m pytest -v") - Run linters if available:
execute("ruff check .") - Run the bundled lint check:
execute("python /skills/code-review/lint_check.py .") - Check against each item in the review checklist
- If any issues found, fix them and re-review
- When everything passes, the review is complete
Helper Scripts
/skills/code-review/lint_check.py— Scans Python files for missing docstrings, long functions (>50 lines), and bareexcept:clauses. Run it viaexecute("python /skills/code-review/lint_check.py [path ...]").
FAQ
What does the code-review skill do?
Perform a structured code review of changes, checking for correctness, style, tests, and potential issues.
How do I install code-review?
Run npx skills add https://github.com/langchain-ai/deepagents --skill code-review in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/code-review/ (personal) or .claude/skills/code-review/ (project).
Which AI agents can use code-review?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is code-review safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains code-review?
It is published by langchain-ai in langchain-ai/deepagents, and it is an official skill from the maker of the technology it covers. It has 213 recorded installs.
More from langchain-ai/deepagents
langgraph-docs
langchain-ai/deepagents
Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.
web-research
langchain-ai/deepagents
Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.
social-media
langchain-ai/deepagents
Drafts engaging social media posts, writes hooks, suggests hashtags, creates thread structures, and generates companion images. Use when the user asks to write a LinkedIn post, tweet, Twitter/X thread, social media caption, social post, or repurpose content for social platforms.
arxiv-search
langchain-ai/deepagents
Searches arXiv for preprints and academic papers, retrieves abstracts, and filters by topic. Use when the user asks to find research papers, search arXiv, look up preprints, find academic articles in physics, math, CS, biology, statistics, or related fields.
blog-post
langchain-ai/deepagents
Writes and structures long-form blog posts, creates tutorial outlines, and optimizes content for SEO with cover image generation. Use when the user asks to write a blog post, article, how-to guide, tutorial, technical writeup, thought leadership piece, or long-form content.
skill-creator
langchain-ai/deepagents
Guide for creating effective skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Use this skill when the user asks to: (1) create a new skill, (2) make a skill, (3) build a skill, (4) set up a skill, (5) initialize a skill, (6) scaffold a skill, (7) update or modify an existing skill, (8) validate a skill, (9) learn about skill structure, (10) understand how skills work, or (11) get guidance on skill design patterns. Trigger on phrases like "create a skill", "new skill", "make a skill", "skill for X", "how do I create a skill", or "help me build a skill".
Popular code quality & workflow skills
grill-me
mattpocock/skills
A relentless interview to sharpen a plan or design.
improve-codebase-architecture
mattpocock/skills
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
handoff
mattpocock/skills
Compact the current conversation into a handoff document for another agent to pick up.
domain-modeling
mattpocock/skills
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
codebase-design
mattpocock/skills
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
diagnosing-bugs
mattpocock/skills
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.