About apple-intelligence
A set of skills for developers adding Apple Intelligence capabilities to apps, including on-device LLMs, visual intelligence, and App Intents. It covers implementation patterns for Siri, Shortcuts, Spotlight, structured output, and model safety.
Key features
- 01On-device model integration and prompting
- 02Structured output and tool calling
- 03Camera-based Visual Intelligence
- 04App Intents for Siri, Shortcuts, and Spotlight
- 05Model availability and safety guidance
Use cases
- 01Adding on-device text generation to an app
- 02Exposing app actions through Siri or Shortcuts
- 03Making app content searchable in Spotlight
- 04Building camera-based visual search
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ rshankras/ claude-code-apple-skills --skill apple-intelligenceAfter installing, type/apple-intelligencein Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
app-intents/advanced-features.mdentities-spotlight.mdintents-basics.mdfoundation-models/models-and-agents.mdsafety-and-guardrails.mdutilities-package.mdDetails
From the project READMEApple 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, evalsmodels-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
- Visual Intelligence
- App Intents
- Local captured docs (optional): if
~/Downloads/docs/containsFoundationModels-Using-on-device-LLM-in-your-app.md,Implementing-Visual-Intelligence-in-iOS.md, orAppIntents-Updates.md, read them for extra detail; skip silently if absent.