apple-intelligence

Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, App Intents, and intelligent assistants. Use when implementing AI-powered features.

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Install skill "apple-intelligence" with this command: npx skills add rshankras/claude-code-apple-skills/rshankras-claude-code-apple-skills-apple-intelligence

Apple Intelligence Skills

Skills for implementing Apple Intelligence features including on-device LLMs, visual recognition, App Intents integration, and intelligent assistants.

When This Skill Activates

Use this skill when the user:

  • Wants to add AI/LLM features to their app
  • Needs on-device text generation or understanding
  • Asks about Foundation Models or Apple Intelligence
  • Wants to implement structured AI output
  • Needs prompt engineering guidance
  • Wants camera-based visual intelligence features
  • Needs Siri, Shortcuts, or Spotlight integration via App Intents
  • Wants to expose app actions or content to the system

Available Skills

foundation-models/

On-device LLM integration with prompt engineering best practices.

  • Model availability checking
  • Session management
  • @Generable structured output
  • Tool calling patterns
  • Snapshot streaming
  • Prompt engineering techniques

visual-intelligence/

Integrate with iOS Visual Intelligence for camera-based search.

  • IntentValueQuery implementation
  • SemanticContentDescriptor handling
  • AppEntity for searchable content
  • Display representations
  • Deep linking from results

app-intents/

App Intents for Siri, Shortcuts, Spotlight, and Apple Intelligence.

  • AppIntent protocol, parameters, perform()
  • AppEntity and entity queries
  • App Shortcuts with voice phrases
  • IndexedEntity and Spotlight indexing
  • Intent modes (background, foreground)
  • Interactive snippets with SnippetIntent
  • Visual intelligence integration
  • Onscreen entities for Siri/ChatGPT
  • Multiple choice API
  • Swift package support

Key Principles

1. Privacy First

  • All processing happens on-device
  • No cloud connectivity required
  • User data never leaves the device

2. Graceful Degradation

  • Always check model availability
  • Provide fallback UI for unsupported devices
  • Handle errors gracefully

3. Efficient Prompting

  • Keep prompts focused and specific
  • Use structured output when possible
  • Respect context window limits (4,096 tokens)

Reference Documentation

  • /Users/ravishankar/Downloads/docs/FoundationModels-Using-on-device-LLM-in-your-app.md
  • /Users/ravishankar/Downloads/docs/Implementing-Visual-Intelligence-in-iOS.md
  • /Users/ravishankar/Downloads/docs/AppIntents-Updates.md

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