foundation-models-on-device

Integrate Apple's on-device FoundationModels framework into iOS 26+ apps for offline text generation and structured data extraction.

2|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/sayasaya8039/ZWG_Terminal --skill foundation-models-on-device-sayasaya8039
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: foundation-models-on-device
Source: https://github.com/sayasaya8039/ZWG_Terminal/tree/main/.claude/skills/foundation-models-on-device
Command: npx skills add https://github.com/sayasaya8039/ZWG_Terminal --skill foundation-models-on-device-sayasaya8039

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the difficulty of building privacy-preserving AI features for iOS apps that require offline functionality and no user data to leave the device, which is not possible with cloud-dependent large language models.

Core Features & Use Cases

  • On-Device Text Generation: Generate summaries, content, and responses directly on the user's device without cloud API calls, ideal for privacy-sensitive use cases like note-taking or personal assistant apps.
  • Structured Data Extraction: Use the @Generable macro to extract typed, structured data from natural language input for form filling, command parsing, or data entry tasks.
  • Custom Tool Calling: Implement domain-specific AI actions like recipe search or calendar lookup by defining custom tools the model can invoke automatically.
  • Snapshot Streaming: Stream partially generated structured responses to update UIs in real time as the model produces output, for responsive user experiences.
  • Use Case Example: A cooking app can use this Skill to extract structured dietary preferences from user natural language input, then generate personalized recipe suggestions entirely on-device without sending user data to external servers.

Quick Start

Use the foundation-models-on-device skill to add a private on-device AI feature to your iOS 26+ app that extracts structured user preferences from natural language input and returns personalized suggestions without sending data to the cloud.

Frequently Asked Questions about foundation-models-on-device

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

FAQPage Schema
How do I implement on-device LLM text generation in SwiftUI without cloud dependency?▼

To implement on-device LLM text generation in SwiftUI, you integrate Apple's FoundationModels framework to run large language model tasks locally on iOS 26+ devices, ensuring user data never leaves the device.

Can I extract structured data from natural language input in iOS 26?▼

You can extract structured data from natural language input in iOS 26 by using the @Generable macro to parse typed information for form filling and command parsing without external API calls.

Does iOS 26 support custom tool calling with Apple Intelligence for offline apps?▼

iOS 26 supports custom tool calling with Apple Intelligence by allowing you to define domain-specific tools like recipe search or calendar lookup that the on-device model invokes automatically.

What is the best way to stream partial LLM responses for real-time SwiftUI updates?▼

The best way to stream partial LLM responses for real-time SwiftUI updates is using snapshot streaming, which pushes partially generated structured data to the UI as the model produces output.

Can I use FoundationModels for privacy-preserving AI features in note-taking apps?▼

You can use FoundationModels to build privacy-preserving AI features for note-taking apps by executing on-device text generation and structured data extraction entirely without cloud dependency.