AxAgent Optimize For Java
Use when writing Java code with dev.axllm:ax for agent optimization, evaluators, judges, optimizer artifacts, BootstrapFewShot, and GEPA.
Install
Install only this skill for Java:
npx skills add https://ax-llm.github.io/ax/java/ --skill 'ax-java-agent-optimize'Published skill file: ax-java-agent-optimize/SKILL.md.
Source
- Source: packages/java/skills/ax-java-agent-optimize/SKILL.md
- Version:
22.0.3
Skill Instructions
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
- Optimize an AxAgent or reusable program component.
- Create evaluator callbacks and persist optimizer artifacts.
- Keep optimization runs bounded by explicit budgets and dataset rows.
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
AxGEPA engine = new AxGEPA(reflectionClient, java.util.Map.of());
var result = engine.optimize(request, evaluator);Relevant API Surface
- Agents And RLM:
Ax.agent,AxAgent - Optimizers:
Ax.optimize,AxBootstrapFewShot,AxGEPA,OptimizerEngine,OptimizerEvaluator
Guardrails
- Start from package examples for exact native syntax before inventing a new call shape.
- Use
provider-apiexamples only when the user explicitly has provider credentials available. - Use
no-keyexamples for deterministic local checks and provider request mapping. - Treat AxIR as the source of generated package truth: if package docs disagree with source code, update the compiler and regenerate packages.
- Do not copy repo-maintainer skills from
tools/*/skills/into user packages.