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Code Reviewer

Listed
matteocervelli·vlatest·backend·MIT

This AI analyzes your backend code for potential bugs, style issues, and vulnerabilities, boosting code quality and security.

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 matteocervelli/llms --skill code-reviewer --full-depth -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

matteocervelli

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No obfuscated payloads: failed

    Contains 1 obfuscated or encoded payload pattern.

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

    What it found

    • .archive/claude-v1/skills/code-reviewer/security-patterns.md:763marshal/pickle payload executed
      data = pickle.loads(untrusted_data)  # DANGEROUS!
  • 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 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 matteocervelli/llms at 1e1f2089eb.

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

Scanned
3 files, 1,614 lines
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 bugs and style issues, and suggests improvements based on common coding best practices. The reviewer aims to improve code quality and reduce the likelihood of errors in backend projects.

When to use it

  • Reviewing a pull request before merging into the main branch.
  • Checking for adherence to specific coding standards within a project.
  • Identifying potential security vulnerabilities in newly written code.
  • Getting a quick second opinion on complex logic or algorithms.

Key capabilities

  • Bug detection
  • Style issue identification
  • Code improvement suggestions
  • Backend focused review

Example prompts

  • "Review this Python function for potential errors: [code snippet]"
  • "Can you check this JavaScript code and suggest improvements to its style?"
  • "Analyze this Go code for security vulnerabilities."

Tips & gotchas

The skill is primarily designed for backend languages. While it may offer some value for other languages, results might be less accurate or comprehensive.