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 alessiorubicini/Apple-Foundation-Models-Agent-Skill --skill apple-foundation-models-skillgit clone --depth 1 https://github.com/alessiorubicini/Apple-Foundation-Models-Agent-SkillWrote 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/alessiorubicini/apple-foundation-models-agent-skill/apple-foundation-models-skill)<a href="https://agentmods.dev/skills/alessiorubicini/apple-foundation-models-agent-skill/apple-foundation-models-skill"><img src="https://agentmods.dev/badge/skills/alessiorubicini/apple-foundation-models-agent-skill/apple-foundation-models-skill/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/alessiorubicini/apple-foundation-models-agent-skill/apple-foundation-models-skill"><img src="https://agentmods.dev/badge/skills/alessiorubicini/apple-foundation-models-agent-skill/apple-foundation-models-skill.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 | $0.00089 | $0.01057 |
| Opus 5 | $0.00044 | $0.00528 |
| Sonnet 5 | $0.00018 | $0.00211 |
| Haiku 4.5 | $0.00009 | $0.00106 |
Grade A, and why
apple-foundation-models-skill 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apple Foundation Models Skill
This skill acts as a router. When handling tasks or queries related to Apple's FoundationModels framework, identify the relevant topic below and load the corresponding reference file before performing any code generation or analysis.
Topic Router
| Topic / API Surface | Target Reference |
|---|---|
| All References Index | references/_index.md |
| Model Access & Availability | system-language-model.md |
| Session & Transcript Lifecycle | session-lifecycle.md |
Structured Output (@Generable) |
guided-generation.md |
| Tool Calling & Capabilities | tool-calling.md |
| Sampling & Options | generation-options.md |
| Streaming UI & Responses | streaming.md |
| Error Handling & Overflow | error-handling.md |
| Swift Concurrency & Actor Isolation | concurrency.md |
| Performance & Prewarming | performance.md |
| Prompt Engineering & Strategy | prompting-techniques.md |
| Prompt Attachments (Images) | prompt-attachments.md |
| Dynamic Profiles & Policies | dynamic-profiles.md |
| Session Properties | session-properties.md |
| Private Cloud Compute (PCC) | private-cloud-compute.md |
| Custom Language Model Providers | custom-language-model-provider.md |
| Framework Glossary | glossary.md |
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/_index.md 2.1 KB
- references/concurrency.md 1.5 KB
- references/custom-language-model-provider.md 4.4 KB
- references/dynamic-profiles.md 6.2 KB
- references/error-handling.md 6.8 KB
- references/generation-options.md 4.7 KB
- references/glossary.md 3.0 KB
- references/guided-generation.md 4.8 KB
- references/performance.md 5.7 KB
- references/private-cloud-compute.md 4.6 KB
- references/prompt-attachments.md 6.5 KB
- references/prompting-techniques.md 10 KB
- references/session-lifecycle.md 7.2 KB
- references/session-properties.md 3.6 KB
- references/streaming.md 6.5 KB
- references/system-language-model.md 4.5 KB
- references/tool-calling.md 6.9 KB
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.
- 11d ago First seen · 39 lines · 89 tokens per session scan A bb36d612928c
apple-foundation-models-skill is a skill published in the GitHub repository alessiorubicini/Apple-Foundation-Models-Agent-Skill (13 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 1,057 once invoked, about $0.0004 per session on Opus 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.
Other skills, from other repositories
apple-foundation-models-conversation-context-builder
Extract context and build continuation prompts for multi-turn conversations.
apple-foundation-models-dynamic-schemas
Build schemas dynamically at runtime for flexible structured output.
apple-foundation-models-error-recovery
Handle context overflow, refusals, rate limits, and generation errors.
apple-foundation-models-generation-tuning
Tune temperature, sampling, seeds, and token limits for optimal output.
apple-foundation-models-playground-learning
Interactive learning examples and playground experiments for Foundation Models.
apple-foundation-models-session-patterns
Create and configure LanguageModelSession for single-turn and multi-turn conversations.