Installable skillMIT

Apple Intelligence Skills

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

BY rshankrasUPDATED Oct 27, 2026
INTENDED FOR◈OpenClawInstall in a listed agent.

instructions.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.
COMPATIBILITY & REFERENCES

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.