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Code Review

Checked
smallnest·vlatest·backend·MIT

Automates Python/Node.js backend code reviews, identifying potential bugs, style issues, and security vulnerabilities quickly.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add smallnest/langgraphgo --skill code-review -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

smallnest

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned smallnest/langgraphgo at 8babee09de.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
8babee09de
Manifest
testdata/skills/code-review/SKILL.md
Scanned
9 files, 3,965 lines
Copies in repo
2 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill provides automated code review capabilities. It analyzes provided code snippets, identifies potential issues like style violations or bugs, and offers suggestions for improvement. The goal is to enhance code quality and reduce the time spent on manual reviews.

When to use it

  • Reviewing pull requests before merging into a main branch.
  • Identifying common coding errors in new feature development.
  • Ensuring adherence to specific style guides within a project.
  • Quickly checking for potential vulnerabilities in code changes.

Key capabilities

  • Automated code analysis
  • Style violation detection
  • Bug identification
  • Suggestion generation

Example prompts

  • "Review this Python function and suggest improvements: [code snippet]"
  • "Check this JavaScript code for style violations according to the Airbnb guide."
  • "Can you find any potential bugs in this Go code?"

Tips & gotchas

The skill's effectiveness depends on the clarity and completeness of the provided code. Providing context, such as the relevant coding standards or project requirements, can improve review accuracy.