Skip to content
TrustedSkillsbeta
Back to all skills

Mobile Instinct V1

Checked
ahmed3elshaer·vlatest·frontend·MIT

Predicts user mobile screen interactions & adjusts UI elements proactively for a smoother, faster experience.

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 ahmed3elshaer/everything-claude-code-mobile --skill mobile-instinct-v1 -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

ahmed3elshaer

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 ahmed3elshaer/everything-claude-code-mobile at d94b24037d.

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

Scanned
2 files, 186 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, mobile-instinct-v1, allows AI agents to understand and adapt to mobile device constraints. It optimizes code for smaller screens and limited resources, ensuring a smooth user experience on smartphones and tablets. The agent can analyze UI designs and generate responsive layouts suitable for various mobile devices.

When to use it

  • Generating mobile website prototypes from design mockups.
  • Optimizing existing web applications for mobile responsiveness.
  • Creating code snippets tailored for specific mobile device resolutions.
  • Adapting a desktop application's UI to function effectively on a tablet.

Key capabilities

  • Responsive layout generation
  • Mobile-first CSS optimization
  • Device resolution adaptation
  • UI design analysis

Example prompts

  • "Generate the HTML and CSS for a mobile landing page based on this Figma design."
  • "Optimize this existing website code to be responsive on mobile devices."
  • "Create a mobile-friendly navigation menu with hamburger icon functionality."

Tips & gotchas

The skill’s effectiveness depends on providing clear UI designs or existing code as input. While it aims for optimization, manual adjustments may still be needed for complex layouts.