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 ComeOnOliver/skillshub --skill axiom-ios-aigit clone --depth 1 https://github.com/ComeOnOliver/skillshubWrote 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/comeonoliver/skillshub/axiom-ios-ai)<a href="https://agentmods.dev/skills/comeonoliver/skillshub/axiom-ios-ai"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-ios-ai/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/comeonoliver/skillshub/axiom-ios-ai"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/axiom-ios-ai.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 | $0.00042 | $0.01171 |
| Opus 5 | $0.00021 | $0.00585 |
| Sonnet 5 | $0.00008 | $0.00234 |
| Haiku 4.5 | $0.00004 | $0.00117 |
Grade A, and why
axiom-ios-ai 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 8d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS Apple Intelligence Router
You MUST use this skill for ANY Apple Intelligence or Foundation Models work.
When to Use
Use this router when:
- Implementing Apple Intelligence features
- Using Foundation Models
- Working with LanguageModelSession
- Generating structured output with @Generable
- Debugging AI generation issues
- iOS 26 on-device AI
AI Approach Triage
First, determine which kind of AI the developer needs:
| Developer Intent | Route To |
|---|---|
| On-device text generation (Apple Intelligence) | Stay here → Foundation Models skills |
| Custom ML model deployment (PyTorch, TensorFlow) | Route to ios-ml → CoreML conversion, compression |
| Computer vision (image analysis, OCR, segmentation) | Route to ios-vision → Vision framework |
| Cloud API integration (OpenAI, etc.) | Route to ios-networking → URLSession patterns |
| System AI features (Writing Tools, Genmoji) | No custom code needed — these are system-provided |
Key boundary: ios-ai vs ios-ml
- ios-ai = Apple's Foundation Models framework (LanguageModelSession, @Generable, on-device LLM)
- ios-ml = Custom model deployment (CoreML conversion, quantization, MLTensor, speech-to-text)
- If developer says "run my own model" → ios-ml. If "use Apple Intelligence" → ios-ai.
Cross-Domain Routing
Foundation Models + concurrency (session blocking main thread, UI freezes):
- Foundation Models sessions are async — blocking likely means missing
awaitor running on @MainActor - Fix here first using async session patterns in foundation-models skill
- If concurrency issue is broader than Foundation Models → also invoke ios-concurrency
Foundation Models + data (@Generable decoding errors, structured output issues):
- @Generable output problems are Foundation Models-specific, NOT generic Codable issues
- Stay here → foundation-models-diag handles structured output debugging
- If developer also has general Codable/serialization questions → also invoke ios-data
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.
- 8d ago First seen · 131 lines · 42 tokens per session scan A 4fff10a1f263
axiom-ios-ai is a skill published in the GitHub repository ComeOnOliver/skillshub (63 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 1,171 once invoked, about $0.0002 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 2026-09-03.
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firebase-ai
Use when setting up firebaseai, generating text/chat with Gemini, streaming AI output, building multimodal prompts, or handling AI errors.