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.
npx skills add Abdullah4AI/apple-developer-toolkit --skill foundation-modelsgit clone --depth 1 https://github.com/Abdullah4AI/apple-developer-toolkitWrote 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.
[](https://agentmods.dev/skills/abdullah4ai/apple-developer-toolkit/foundation-models)<a href="https://agentmods.dev/skills/abdullah4ai/apple-developer-toolkit/foundation-models"><img src="https://agentmods.dev/badge/skills/abdullah4ai/apple-developer-toolkit/foundation-models/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/abdullah4ai/apple-developer-toolkit/foundation-models"><img src="https://agentmods.dev/badge/skills/abdullah4ai/apple-developer-toolkit/foundation-models.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once 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 |
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.
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
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.
- 1mo ago First seen · 49 lines · 64 tokens per session scan A f02029521040
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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