Borrowing it
Nothing to install: this file belongs to dosco/aithy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dosco/aithy/main/.claude/skills/ax-gen/SKILL.mdgit clone --depth 1 https://github.com/dosco/aithyWrote 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/dosco/aithy/ax-gen)<a href="https://agentmods.dev/skills/dosco/aithy/ax-gen"><img src="https://agentmods.dev/badge/skills/dosco/aithy/ax-gen/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/dosco/aithy/ax-gen"><img src="https://agentmods.dev/badge/skills/dosco/aithy/ax-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00086 | $0.05138 |
| Opus 5.5 | $0.00034 | $0.02055 |
| Sonnet 5.5 | $0.00017 | $0.01028 |
| Haiku 4.5 | $0.00009 | $0.00514 |
Grade A, and why
ax-gen 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.
How it starts
The opening of the file, as written. The whole thing — 564 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AxGen Codegen Rules (@ax-llm/ax)
Use this skill to generate AxGen code. Prefer short, modern, copyable patterns. Do not write tutorial prose unless the user explicitly asks for explanation.
Use the ax-mcp skill when AxGen attaches native MCP clients or consumes MCP
prompts, resources, tools, tasks, subscriptions, authentication, or events.
Use These Defaults
- Use
ax(...)factory, notnew AxGen(...). - Always pass an AI instance from
ai(...)as the first argument toforward(). - Streaming uses
streamingForward(), notforward()with a stream option. - Use schema validation for field shape and constraints.
- Use
addAssert(...)for whole-output hard invariants with correction retries. - Use
addStreamingAssert(...)for partial streaming hard invariants with fail-fast per-attempt correction retries. - Use
bestOfN(...)/refine(...)for reward-scored complete outputs. - Step hook mutations are applied at the next step boundary (pending pattern).
stopFunctionaccepts a string or string[] for multiple stop functions.- Multi-step continues until: all outputs filled, stop function called, or
maxStepsreached.
Canonical Pattern
import { ai, ax, s } from '@ax-llm/ax';
const llm = ai({
name: 'openai',
apiKey: process.env.OPENAI_APIKEY!,
});
// Inline signature
const gen = ax('input:string -> output:string, reasoning:string');
// Reusable signature
const sig = s('question:string, context:string[] -> answer:string');
const gen2 = ax(sig);
// With options
const gen3 = ax('input -> output', {
description: 'A helpful assistant',
maxRetries: 3,
maxSteps: 10,
temperature: 0.7,
});
const result = await gen.forward(llm, { input: 'Hello world' });
console.log(result.output);
Signatures from zod / valibot / arktype
ax() accepts any signature built with f(), and f().input() / .output() accept Standard Schema v1 validators directly — per-field or a whole z.object({...}):
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 Changed · +68 lines · +24 tokens per session b1dfd2fbbcb2
- 1mo ago First seen · 496 lines · 62 tokens per session scan A 960b12da750a
ax-gen is a skill published in the GitHub repository dosco/aithy (108 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 86 tokens to every session and 5,138 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 2026-08-30.
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Use when writing C++ code with axllm for GEPA, Pareto tradeoffs, reflection clients, metric budgets, optimizer state, and artifacts.
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model-context
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build-mcp-server
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developing-genkit-js
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