AxAgent Optimize For C++

Use when writing C++ code with axllm for agent optimization, evaluators, judges, optimizer artifacts, BootstrapFewShot, and GEPA.

Install

Install only this skill for C++:

Shell

npx skills add https://ax-llm.github.io/ax/cpp/ --skill 'ax-cpp-agent-optimize'

Published skill file: ax-cpp-agent-optimize/SKILL.md.

Source

Source: packages/cpp/skills/ax-cpp-agent-optimize/SKILL.md
Version: 22.0.3

Skill Instructions

This skill helps an agent write C++ code with the generated Ax package axllm. 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: C++.
Package: axllm.
Package API docs: API.md and axir-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

C++

axllm::AxGEPA engine(reflection_client, options);
auto result = engine.optimize(request, evaluator);

Relevant API Surface

Agents And RLM: axllm::agent, axllm::AxAgent
Optimizers: axllm::optimize, axllm::AxBootstrapFewShot, axllm::AxGEPA, axllm::OptimizerEngine, axllm::OptimizerEvaluator

Guardrails

Start from package examples for exact native syntax before inventing a new call shape.
Use provider-api examples only when the user explicitly has provider credentials available.
Use no-key examples 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.