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Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, App Intents, and intelligent assistants. Use when implementing AI-powered features.
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Basierend auf der SOC-Berufsklassifikation
TDD and testing skills for iOS/macOS apps. Covers characterization tests, TDD workflows, test contracts, snapshot tests, test infrastructure, and deterministic quality gates (fitness functions, coverage ratchet, mutation testing). Use for test-driven development, adding tests to existing code, or building test infrastructure.
Set up SwiftUI visual regression testing with swift-snapshot-testing. Generates snapshot test boilerplate and CI configuration. Use for UI regression prevention.
Gate test coverage with a ratchet — a committed baseline that coverage may never drop below and only ever rises. Ships a coverage-gate script (xccov-based) plus an advisory CRAP report (complexity × uncovered). Use when agent-written code needs a deterministic "tests were actually written" check.
Enforce complexity and size limits on Swift code with SwiftLint threshold rules — cyclomatic complexity, function/type/file length, parameter count — adopted via a violations baseline so existing code never blocks. Use when agent-written code needs deterministic size constraints.
Swift language patterns and best practices including concurrency, performance, and modern idioms. Use for Swift language-level code review or architecture guidance.
Write architecture fitness functions — deterministic tests that enforce a project's hard rules (module boundaries, offline guarantees, content contracts) from inside its own test target. Use when a constraint lives only in prose (CLAUDE.md, code review) and should become un-arguable.
| 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 | "2026-07-16T00:00:00.000Z" |
| review_by | "2027-06-22T00:00:00.000Z" |
| os_version | iOS 27 / macOS 27 |
Skills for implementing Apple Intelligence features including on-device LLMs, visual recognition, App Intents integration, and intelligent assistants.
Use this skill when the user:
On-device LLM integration with prompt engineering best practices.
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 rulesIntegrate with iOS Visual Intelligence for camera-based search.
App Intents for Siri, Shortcuts, Spotlight, and Apple Intelligence.
model.contextSize, never hardcode (4,096 first-gen on-device; 8,192 iOS 27 on-device; 32,000 Private Cloud Compute)~/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.