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 Kasempiternal/axiom-v2 --skill ax-foundation-modelsgit clone --depth 1 https://github.com/Kasempiternal/axiom-v2Wrote 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/kasempiternal/axiom-v2/ax-foundation-models)<a href="https://agentmods.dev/skills/kasempiternal/axiom-v2/ax-foundation-models"><img src="https://agentmods.dev/badge/skills/kasempiternal/axiom-v2/ax-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/kasempiternal/axiom-v2/ax-foundation-models"><img src="https://agentmods.dev/badge/skills/kasempiternal/axiom-v2/ax-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 | $0.00039 | $0.02656 |
| Opus 5 | $0.00019 | $0.01328 |
| Sonnet 5 | $0.00008 | $0.00531 |
| Haiku 4.5 | $0.00004 | $0.00266 |
Grade A, and why
ax-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 10d 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Foundation Models — On-Device AI for Apple Platforms
Quick Patterns
Basic Session
import FoundationModels
let session = LanguageModelSession(instructions: "You are a helpful assistant.")
let response = try await session.respond(to: userInput)
response.content // plain String
@Generable Structured Output
@Generable
struct Person {
@Guide(description: "Full name")
let name: String
@Guide(.range(1...120))
let age: Int
}
let response = try await session.respond(to: "Generate a person", generating: Person.self)
response.content // type-safe Person
Streaming
let stream = session.streamResponse(to: prompt, generating: Itinerary.self)
for try await partial in stream {
self.itinerary = partial // PartiallyGenerated — all properties optional
}
Tool Calling
struct GetWeatherTool: Tool {
let name = "getWeather"
let description = "Retrieve latest weather for a city"
@Generable
struct Arguments {
@Guide(description: "The city to fetch weather for")
var city: String
}
func call(arguments: Arguments) async throws -> ToolOutput {
let weather = try await WeatherService.shared.weather(for: /* geocoded location */)
return ToolOutput("\(arguments.city): \(weather.currentWeather.temperature.value) degrees")
}
}
let session = LanguageModelSession(tools: [GetWeatherTool()])
Availability Check (mandatory)
switch SystemLanguageModel.default.availability {
case .available:
let session = LanguageModelSession()
case .unavailable(let reason):
// Show: "AI features require Apple Intelligence"
}
Error Handling (mandatory)
do {
let response = try await session.respond(to: prompt)
} catch LanguageModelSession.GenerationError.exceededContextWindowSize {
session = condensedSession(from: session) // see Context Management
} catch LanguageModelSession.GenerationError.guardrailViolation {
showMessage("I can't help with that request")
} catch LanguageModelSession.GenerationError.unsupportedLanguageOrLocale {
showMessage("Language not supported")
}
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.
- 10d ago First seen · 300 lines · 39 tokens per session scan A d4528d98adf0
ax-foundation-models is a skill published in the GitHub repository Kasempiternal/axiom-v2 (4 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 2,656 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 2026-08-31.
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