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/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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rshankras-apple-skills
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$ npx -y skills add rshankras/claude-code-apple-skills --skill apple-intelligence --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/apple-intelligence

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

apple-intelligence.SKILL.md
name: apple-intelligence
description: Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, App Intents, and intelligent assistants. Use when implementing AI-powered features.
allowed-tools: [Read, Write, Edit, Glob, Grep, Bash, AskUserQuestion]
last_verified: 2026-07-16
review_by: 2027-06-22
os_version: iOS 27 / macOS 27

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 (property-order + schema-injection rules)
  • Tool calling patterns
  • Snapshot streaming
  • Prompt engineering techniques
  • `safety-and-guardrails.md` — model limits, the instructions-over-prompts hierarchy, guardrail handling, the four-layer safety stack, evals
  • `models-and-agents.md` — Private Cloud Compute, LanguageModel protocol (third-party backends), vision input, DynamicProfile agents, tool-calling modes, KV-cache rules

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

  • On-device processing by default; Private Cloud Compute extends capacity without storing prompts (no account/API keys — WWDC26 241)
  • When routing to less-private backends, redact context first (see foundation-models/models-and-agents.md)

2. Graceful Degradation

  • Always check model availability
  • Provide fallback UI for unsupported devices
  • Handle errors gracefully (incl. guardrail violations — silent for proactive features, explained for user-initiated)

3. Efficient Prompting

  • Keep prompts focused and specific
  • Use structured output when possible
  • Respect context window limits — query `model.contextSize`, never hardcode (4,096 first-gen on-device; 8,192 iOS 27 on-device; 32,000 Private Cloud Compute)

Reference Documentation

  • [Foundation Models](https://developer.apple.com/documentation/foundationmodels)
  • [Visual Intelligence](https://developer.apple.com/documentation/visualintelligence)
  • [App Intents](https://developer.apple.com/documentation/appintents)
  • Local captured docs (optional): if `~/Downloads/docs/` contains `FoundationModels-Using-on-device-LLM-in-your-app.md`, `Implementing-Visual-Intelligence-in-iOS.md`, or `AppIntents-Updates.md`, read them for extra detail; skip silently if absent.
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Ships withrshankras-apple-skills

A collection of Claude Code skills for iOS, macOS, watchOS, visionOS, and Apple platform development. These skills help you plan and build apps, maintain code quality, ensure HIG compliance, and guide you from idea to App Store.

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MIT
License
16d ago
Last commit
9mo ago
Created

Repo: rshankras/claude-code-apple-skills

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