Skip to content
TrustedSkillsbeta
Back to all skills

Review Code

Checked
catlog22·vlatest·agents·MIT

Analyzes code for potential bugs, style issues, and suggests improvements based on established best practices.

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 catlog22/claude-code-workflow --skill review-code -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

catlog22

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 catlog22/claude-code-workflow at 07491b04ac.

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

Commit
07491b04ac
Manifest
.claude/skills/review-code/SKILL.md
Scanned
21 files, 3,859 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 enables AI agents to perform code reviews within the catlog22/claude-code-workflow ecosystem. It allows the agent to analyze submitted code changes, identify potential bugs or inefficiencies, and provide structured feedback before implementation is finalized.

When to use it

  • Before merging a pull request to ensure no critical logic errors slip into production.
  • During the development phase to get immediate suggestions for refactoring complex functions.
  • When onboarding new team members to maintain consistent coding standards across the project.
  • To validate that security best practices are followed in newly written scripts.

Key capabilities

  • Analyzes code changes for logical errors and performance bottlenecks.
  • Integrates seamlessly with the claude-code-workflow environment.
  • Provides actionable feedback on style, readability, and maintainability.
  • Supports iterative review cycles within a single workflow session.

Example prompts

  • "Review this function for potential race conditions and suggest fixes."
  • "Analyze the recent changes in the authentication module against our security guidelines."
  • "Provide a summary of code quality issues found in this pull request before I merge it."

Tips & gotchas

Ensure your AI agent has read access to the repository history and current branch state for accurate context. Limit review scope to specific files or functions if the entire codebase is too large for a single pass, as this may reduce the depth of analysis.