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Code Review Pro

Checked
onewave-ai·vlatest·backend·MIT

Automated code review focusing on performance, security vulnerabilities, and adherence to best practices in backend systems.

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 onewave-ai/claude-skills --skill code-review-pro -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

onewave-ai

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 onewave-ai/claude-skills at f317e08649.

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

Commit
f317e08649
Manifest
code-review-pro/SKILL.md
Scanned
2 files, 147 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

The code-review-pro skill enables AI agents to analyze, evaluate, and provide feedback on code written in various programming languages. It identifies potential bugs, performance issues, security vulnerabilities, and style inconsistencies, helping developers improve the quality of their code.

When to use it

  • Before merging a pull request to ensure code meets quality standards
  • To identify hidden bugs or inefficiencies in legacy codebases
  • When preparing for code audits or compliance checks

Key capabilities

  • Detects syntax errors and logical flaws
  • Suggests performance optimizations
  • Highlights security risks like SQL injection or XSS vulnerabilities
  • Enforces coding style and best practices

Example prompts

  • "Review this Python script for potential bugs and suggest improvements."
  • "Check the JavaScript function for security vulnerabilities."
  • "Analyze this C++ code for memory leaks and optimize where possible."

Tips & gotchas

  • Ensure the code being reviewed is well-formatted and includes relevant context.
  • While the skill provides strong recommendations, always validate suggestions with manual testing or peer review.