Ax is a TypeScript-first programming framework for building applications with large language models through typed generation, agents, workflows, and optimization tools. It is intended for developers who want one model for LLM programs across TypeScript, Python, Java, C++, Go, Rust, and other runtimes.
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 ax-llm/ax --skill ax-java-gengit clone --depth 1 https://github.com/ax-llm/axWrote 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/ax-llm/ax/ax-java-gen)<a href="https://agentmods.dev/skills/ax-llm/ax/ax-java-gen"><img src="https://agentmods.dev/badge/skills/ax-llm/ax/ax-java-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/ax-llm/ax/ax-java-gen"><img src="https://agentmods.dev/badge/skills/ax-llm/ax/ax-java-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 | $0.00049 | $0.05957 |
| Opus 5.5 | $0.00020 | $0.02383 |
| Sonnet 5.5 | $0.00010 | $0.01191 |
| Haiku 4.5 | $0.00005 | $0.00596 |
Grade A, and why
ax-java-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 yesterday.
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.
Copies of this mod
2 near-identical copies found in the catalogue:
- ax-rust-gen — 89% identical, 46 lines differ
- ax-python-gen — 80% identical, 48 lines differ
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AxGen Structured Generation For Java
This skill helps an agent write Java code with the generated Ax package dev.axllm:ax. Use the generated package API, examples, and manifests; do not import TypeScript-only APIs unless you are editing the TypeScript package.
When To Use
- Build a structured generation program from a signature.
- Attach typed tools or MCP-derived tools to a generation call.
- Generate multiple validated structured samples and select a winner with a native callback.
- Use package examples for no-key scripted clients and provider-api calls.
Package Facts
- Language: Java.
- Package:
dev.axllm:ax. - Package API docs:
API.mdandaxir-api.json. - Capability manifest:
axir-capabilities.json. - Runnable examples:
examples/. - Real network support: yes.
- Scripted no-key transport support: yes.
- Runtime profiles:
javascript-quickjs,python-pyodide.
Core Pattern
AxGen program = Ax.ax("question:string -> answer:string");
var out = program.forward(llm, java.util.Map.of("question", "What is Ax?"));
OpenAI Decisions
The openai-decisions provider uses /v1/decisions with gpt-6-luna by default. Required boolean fields become predicates; required class fields become choices; score fields become labelled native rubrics. Use normal AxGen signatures with (evidence) to retain probabilities, provider-selected values, native confidence, and trusted provenance; use (evidence, refusal return) for an answered/refused union. See the Typesafe/Jev skill for decision evidence and reranking across both providers. trueThreshold (or true_threshold) defaults to 0.5, is finite in [0,1], and uses an inclusive comparison. Field value descriptions become criteria instructions or choice descriptions. Raw answers remain in providerMetadata.openaiDecisions.answers; usage uses existing program APIs.
Use Ax.openaiDecisions for explicit provider request shapes and native JSON input. Its create operation (Go: Create) accepts input and an ordered questions array. Each question has string instructions and an optional unique string name; unnamed answers retain name: null. Predicate returns probability. Choice requires 2-255 string or boolean choices and returns choice, confidence, and probabilities. Score requires 2-10 explicitly labelled levels and returns a fractional zero-based score, confidence, and probabilities. Handle type: refusal before accessing answer values. Preserve full model, answer order, and usage.
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.
- yesterday Changed 9e21498df226
- 3d ago Changed 52fde1bd9a61
- 5d ago Changed d6f97cb55634
- 8d ago Changed f7c4901c560e
- 9d ago Changed · +10 lines eb1bb9aab46e
- 10d ago Changed 7261d2f712f5
- 16d ago Changed · +7 lines d27b8b9050f4
- 19d ago Changed · +10 lines 1dd87db6e19b
- 20d ago Changed · +14 lines e8318dffc4a4
- 21d ago First seen · 95 lines · 49 tokens per session scan A 1dc709e956ea
ax-java-gen is a skill published in the GitHub repository ax-llm/ax (2,967 stars, last pushed 2d ago), licensed Apache-2.0. It adds 49 tokens to every session and 5,957 once invoked, about $0.0002 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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