Skip to content
TrustedSkillsbeta
Back to all skills

Apple On Device Ai

Checked
dpearson2699·vlatest·other

Analyzes local apple device data (photos, notes, health) to provide personalized insights and automated actions offline.

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 dpearson2699/swift-ios-skills --skill apple-on-device-ai -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

dpearson2699

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 dpearson2699/swift-ios-skills at 8d90fd121a.

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

Commit
8d90fd121a
Manifest
skills/apple-on-device-ai/SKILL.md
Scanned
6 files, 1,827 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 leverage Apple's on-device machine learning capabilities. It allows for real-time processing of data directly on the user’s device, such as image recognition, natural language understanding, and predictive text without requiring a network connection or sending data to external servers. This enhances privacy and reduces latency compared to cloud-based solutions.

When to use it

  • Image Classification: Classify objects in photos taken with the device's camera, useful for automated tagging or content filtering.
  • Real-time Translation: Provide instant translation of spoken language during conversations without internet access.
  • Predictive Text Input: Offer contextually relevant word suggestions as a user types, improving typing speed and accuracy.
  • Offline Voice Commands: Process voice commands for device control even when offline.

Key capabilities

  • On-device machine learning inference
  • Image recognition
  • Natural language processing (NLP)
  • Predictive text generation
  • Real-time translation

Example prompts

  • "Classify this image." (followed by providing an image)
  • "Translate 'Hello, how are you?' into Spanish."
  • "Suggest the next word in this sentence: 'The cat sat on the...'"
  • “What is the dominant color of this photo?”

Tips & gotchas

  • Requires access to Apple’s Core ML framework and compatible device hardware.
  • Model size and complexity can impact device performance; optimize models for efficiency.