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Team Frontend

Checked
catlog22·vlatest·frontend·MIT

Generates clean, maintainable React components and code snippets based on design specifications and user stories.

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 team-frontend -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
.codex/skills/team-frontend/SKILL.md
Scanned
22 files, 2,560 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 enables AI agents to generate frontend code, likely for web applications. It facilitates the creation of user interfaces and interactive elements based on provided instructions or designs. The specific functionality includes generating code snippets and potentially complete components.

When to use it

  • Rapid prototyping: Quickly create basic UI layouts and components to test design concepts.
  • Component generation: Generate reusable frontend components from descriptions, reducing repetitive coding tasks.
  • Code scaffolding: Automate the creation of initial project structures or boilerplate code for new frontend projects.
  • UI implementation: Translate design specifications into functional frontend code.

Key capabilities

  • Frontend code generation
  • Component creation
  • Potential for UI layout generation (implied)

Example prompts

  • "Generate a React component for a simple login form."
  • "Create the HTML and CSS for a navigation bar with three links."
  • "Build a Vue.js component that displays a list of items fetched from an API."

Tips & gotchas

The quality of generated code depends heavily on the clarity and specificity of the prompt. Providing detailed instructions or design specifications will yield better results.