foundation-models

foundation-models is a skill for Claude Code, Codex from Abdullah4AI/apple-developer-toolkit. It costs 64 tokens per session (397 once invoked), scanned A, original, MIT.

A guide to Apple’s Foundation Models framework for running text-generation AI on supported devices. It covers normal and streaming responses, structured results, and checking whether the device has an available model.

In plain words
What is it for?
Use it to add on-device text generation, live streamed responses, or structured AI-created content such as recipe suggestions.
Why use it?
It shows how to handle devices where Apple’s on-device AI is unavailable and how to request predictable data instead of only free-form text.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to add on-device text generation, live streamed responses, or structured AI-created content such as recipe suggestions.

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Install with agentmods
npx agentmods add skills/abdullah4ai/apple-developer-toolkit/foundation-models
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Abdullah4AI/apple-developer-toolkit --skill foundation-models
Clone the repo
git clone --depth 1 https://github.com/Abdullah4AI/apple-developer-toolkit

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 397 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.00397
Opus 5.5 $0.00026 $0.00159
Sonnet 5.5 $0.00013 $0.00079
Haiku 4.5 $0.00006 $0.00040

Measured 1mo ago against content hash f02029521040, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

foundation-models scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

swiftship/internal/skills/data/features/foundation-models/SKILL.md · 49 lines

What it actually says

Foundation Models

APPLE ON-DEVICE AI (FoundationModels — iOS 26+): FRAMEWORK: import FoundationModels

AVAILABILITY CHECK (MANDATORY — model may not be available on all devices): guard case .available = SystemLanguageModel.default.availability else { // Show "This feature requires Apple Intelligence" message return }

BASIC TEXT GENERATION: let session = LanguageModelSession() let response = try await session.respond(to: "Summarize this text: (userText)") print(response.content)

STREAMING GENERATION: let stream = session.streamResponse(to: prompt) for try await partial in stream { displayText += partial.text }

STRUCTURED OUTPUT with @Generable: @Generable struct RecipeSuggestion { @Guide(description: "Name of the dish") var name: String @Guide(description: "Estimated prep time in minutes") var prepTime: Int @Guide(description: "Main ingredients") var ingredients: [String] }

let session = LanguageModelSession() let recipe: RecipeSuggestion = try await session.respond( to: "Suggest a quick pasta dish", generating: RecipeSuggestion.self )

SESSION INSTRUCTIONS (system prompt): let session = LanguageModelSession(instructions: "You are a helpful cooking assistant. Keep responses concise.")

GUARDRAILS:

  • Model output is filtered by Apple's safety system
  • No internet required — fully on-device
  • Context window is limited (~4K tokens typical) — keep prompts concise
  • Use session.respond() for single turns, keep session for multi-turn conversations
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 49 lines · 64 tokens per session scan A f02029521040

Subscribe to this mod's changes

foundation-models is a skill published in the GitHub repository Abdullah4AI/apple-developer-toolkit (11 stars, last pushed 3d ago), licensed MIT. It adds 64 tokens to every session and 397 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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