skills.rest
jtvaris
jtvarisCOMMUNITY
Explore all skills by this author →
GitHub

apple-intelligence

Integrate on-device Foundation Models with session management and structured outputs.

Updated Mar 15, 2026
Search Tags:#llm#foundation-models#privacy#on-device#prompt-engineering#structured-output
One-click install
npx skills add https://github.com/jtvaris/sunday-night-dynasty --skill apple-intelligence-jtvaris
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: apple-intelligence
Source: https://github.com/jtvaris/sunday-night-dynasty/tree/main/.agents/skills/apple-intelligence
Command: npx skills add https://github.com/jtvaris/sunday-night-dynasty --skill apple-intelligence-jtvaris

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Foundation Models on-device enable private, low-latency AI capabilities within apps, eliminating reliance on cloud services and protecting user data.

Core Features & Use Cases

  • On-device language model integration for privacy-preserving AI features.
  • Structured output with @Generable types and tool calling.
  • Multi-turn conversations and session management for intelligent assistants.

Quick Start

Create a LanguageModelSession and generate a response using respond(to:).

Frequently Asked Questions about apple-intelligence

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate on-device Foundation Models into my app?▼

To integrate on-device Foundation Models, create a LanguageModelSession and generate responses using the respond(to:) method. This enables private, low-latency AI capabilities directly within your application.

What are on-device Foundation Models used for in mobile applications?▼

On-device Foundation Models enable private AI capabilities without cloud services. Use cases include on-device text generation, structured data extraction, multi-turn conversations, and tool calling.

Can I get structured data extraction from an on-device language model?▼

Yes, you can achieve structured data extraction using @Generable types for structured outputs. This allows the on-device language model to return organized, typed data for your application.

Does on-device AI require cloud services or network connectivity?▼

No, on-device AI eliminates reliance on cloud services. By using Foundation Models locally, applications protect user data and provide low-latency AI capabilities without network connectivity.

What is the best way to manage multi-turn conversations with an on-device language model?▼

The best way to manage multi-turn conversations is through LanguageModelSession management. This approach maintains context across interactions to build intelligent assistants with on-device Foundation Models.

Why do I need availability checks before using on-device Foundation Models?▼

Availability checks are required because on-device Foundation Models depend on specific hardware capabilities. Verifying availability ensures your app degrades gracefully when local AI processing is unsupported.

Related Skills

Explore More Software Engineering Skills→
DengNaichenDengNaichen
34

axiom-ai

Implement Apple Intelligence features with LanguageModelSession and @Generable structured output.

Community
Advanced
mintuzmintuz
21

local-ai-models

Integrate on-device AI models in iOS apps using Foundation Models and MLX Swift.

Community
Advanced
Prathviraj-jadhavPrathviraj-jadhav

LLM

Integrate and orchestrate large language models for multi-turn AI applications.

Community
Advanced
gustavscirulisgustavscirulis
114

apple-intelligence

Integrate Apple Foundation Models, Visual Intelligence, and App Intents for on-device AI features.

Community
Advanced