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Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, App Intents, and intelligent assistants.
Passed 19 of 22 test cases with the skill, and 13 of 22 without it.
and 4 more in the full report
6 fixed13 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
I'm building an iOS app in Swift and want to use Apple's local LLM features to convert user meeting transcripts into structured action items. How should I initialize the model session and define a strongly-typed schema so the output strictly conforms to a Swift struct without breaking model context limits?
| Checked | Without skill | With skill |
|---|---|---|
| Uses the @Generable macro to define the structured output schema. | Missed | Passed |
| Queries model.contextSize dynamically rather than hardcoding context window limits. | Missed | Passed |
The instructions your model reads when the skill loads.
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.
test cases passed, vs 13 / 22 without
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