Agent-Skills.md

Agent Skills: Foundation Models

Use when implementing on-device AI with Apple's Foundation Models framework (iOS 26+), building summarization/extraction/classification features, or using @Generable for type-safe structured output.

UncategorizedID: johnrogers/claude-swift-engineering/foundation-models

Repository

johnrogers/claude-swift-engineering
johnrogersLicense: MIT
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pnpm dlx add-skill https://github.com/johnrogers/claude-swift-engineering/tree/HEAD/plugins/swift-engineering/skills/foundation-models

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plugins/swift-engineering/skills/foundation-models/SKILL.md

Skill Metadata

Name
foundation-models
Description
Use when implementing on-device AI with Apple's Foundation Models framework (iOS 26+), building summarization/extraction/classification features, or using @Generable for type-safe structured output.

Foundation Models

Apple's on-device AI framework providing access to a 3B parameter language model for summarization, extraction, classification, and content generation. Runs entirely on-device with no network required.

Overview

Foundation Models enable intelligent text processing directly on device without server round-trips, user data sharing, or network dependencies. The core principle: leverage on-device AI for specific, contained tasks (not for general knowledge).

Reference Loading Guide

ALWAYS load reference files if there is even a small chance the content may be required. It's better to have the context than to miss a pattern or make a mistake.

| Reference | Load When | |-----------|-----------| | Getting Started | Setting up LanguageModelSession, checking availability, basic prompts | | Structured Output | Using @Generable for type-safe responses, @Guide constraints | | Tool Calling | Integrating external data (weather, contacts, MapKit) via Tool protocol | | Streaming | AsyncSequence for progressive UI updates, PartiallyGenerated types | | Troubleshooting | Context overflow, guardrails, errors, anti-patterns |

Core Workflow

  1. Check availability with SystemLanguageModel.default.availability
  2. Create LanguageModelSession with optional instructions
  3. Choose output type: plain String or @Generable struct
  4. Use streaming for long generations (>1 second)
  5. Handle errors: context overflow, guardrails, unsupported language

Model Capabilities

| Use Case | Foundation Models? | Alternative | |----------|-------------------|-------------| | Summarization | Yes | - | | Extraction (key info) | Yes | - | | Classification | Yes | - | | Content tagging | Yes (built-in adapter) | - | | World knowledge | No | ChatGPT, Claude, Gemini | | Complex reasoning | No | Server LLMs |

Platform Requirements

  • iOS 26+, macOS 26+, iPadOS 26+, visionOS 26+
  • Apple Intelligence-enabled device (iPhone 15 Pro+, M1+ iPad/Mac)
  • User opted into Apple Intelligence

Common Mistakes

  1. Using Foundation Models for world knowledge — The 3B model is trained for on-device tasks only. It won't know current events, specific facts, or "who is X". Use ChatGPT/Claude for that. Keep prompts to: summarizing user's own content, extracting info, classifying text.

  2. Blocking the main thread — LanguageModelSession calls must run on a background thread or async context. Blocking the main thread locks UI. Always use Task { } or background queue.

  3. Ignoring context overflow — The model has finite context. If the user pastes a 50KB document, it will fail silently or truncate. Check input length and trim/truncate proactively.

  4. Forgetting to check availability — Not all devices support Foundation Models. Check SystemLanguageModel.default.availability before using. Graceful degradation is required.

  5. Ignoring guardrails — The model won't answer harmful queries. Instead of fighting it, design prompts that respect safety guidelines. Rephrasing requests usually works.