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 agentmods add skills/ax-llm/ax/ax-java-llmnpx skills add ax-llm/ax --skill ax-java-llmgit clone --depth 1 https://github.com/ax-llm/axWhat 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 | $0.00039 | $0.00703 |
| Opus 5 | $0.00019 | $0.00351 |
| Sonnet 5 | $0.00008 | $0.00141 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
ax-java-llm 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 today.
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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ax LLM Quick Reference 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
- Start a generated-language Ax program from package docs or examples.
- Translate the Ax mental model into the target package without TypeScript-only imports.
- Choose the native package entrypoints for signatures, providers, generators, agents, flows, and optimizers.
- Find ordered or adaptive provider-balancing guidance in the language-specific AI skill.
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
import dev.axllm.ax.*;
var llm = Ax.ai("openai", java.util.Map.of("apiKey", System.getenv("OPENAI_API_KEY")));
Relevant API Surface
- Signatures:
Ax.s,Ax.f,AxSignature - AxGen:
Ax.ax,AxGen - AxAI:
Ax.ai,Ax.getSupportedAIModels,OpenAICompatibleClient.CredentialRequest,OpenAICompatibleClient.CredentialProvider,AxChatStream,OpenAICompatibleClient,OpenAIResponsesClient,GoogleGeminiClient,AnthropicClient,Map<String, Object>,AxUsageEvent,AxUsageObserver,AxGlobals.setUsageObserver,AxRuntimeHooks,AxRateLimitInfo,AxRateLimiter,AxTracer,AxMeter,AxGlobals,AxGlobals.setRateLimiter,AxGlobals.setTracer,AxGlobals.setMeter,AxBalancer,AxBalancerAdaptiveStrategy,AxBalancerStatsStore,AxInMemoryBalancerStatsStore,AxBalancerAdaptive.createRouteStats,AxBalancerAdaptive.updateRouteStats,AxBalancerAdaptive.sampleRouteHealth,MultiServiceRouter,ProviderRouter - Agents And RLM:
Ax.agent,AxAgent - Flow:
Ax.flow,AxFlow - Optimizers:
Ax.optimize,Ax.playbook,AxPlaybook,AxBootstrapFewShot,AxGEPA,OptimizerEngine,OptimizerEvaluator
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.
- today Changed fa98492f907b
- 3d ago First seen · 51 lines · 39 tokens per session scan A dc82598f22d4
ax-java-llm is a skill published in the GitHub repository ax-llm/ax (2,890 stars, last pushed yesterday), licensed Apache-2.0. It adds 39 tokens to every session and 703 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 2026-08-30.
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