AxAgent Optimize For C++

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.
• Mine grounded weaknesses from failed agent tasks and keep only playbook proposals that pass the verification gate.
• 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

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::playbook, axllm::AxPlaybook, 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.