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Hig Components Content

Checked
raintree-technology·vlatest·frontend·MIT

Analyzes high-impact website components to identify content gaps and opportunities for optimization using Raintree Technology's AI.

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 raintree-technology/hig-doctor --skill hig-components-content -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

raintree-technology

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 raintree-technology/apple-hig-skills at 3ec08f5a6f.

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

Commit
3ec08f5a6f
Manifest
skills/hig-components-content/SKILL.md
Scanned
9 files, 403 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 access to Apple Human Interface Guidelines (HIG) component information. It allows AI agents to retrieve details about specific UI components, including their purpose, usage recommendations, and accessibility considerations. The goal is to help developers build user interfaces that adhere to Apple's design standards.

When to use it

  • Generating documentation for iOS or macOS applications.
  • Providing guidance on implementing specific UI elements in a project.
  • Ensuring consistency with Apple’s design language across multiple apps.
  • Troubleshooting UI component behavior and finding relevant HIG information.

Key capabilities

  • Access to Apple Human Interface Guidelines (HIG) content.
  • Information retrieval about individual UI components.
  • Provides purpose, usage recommendations, and accessibility considerations for each component.

Example prompts

  • "Tell me about the UISlider component."
  • “What are the guidelines for using UITableView?”
  • "How should I handle accessibility with UIButtons?"

Tips & gotchas

The skill's effectiveness depends on the accuracy and completeness of the underlying HIG data. Results may vary depending on the specific version of iOS or macOS being targeted.