Use when writing C++ code with `axllm` for deciding between context maps, trajectory context policy, offline optimization (ACE/GEPA), and memory recall for long-context agents.
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.
axllm.API.md and axir-api.json.axir-capabilities.json.examples/.javascript-quickjs, python-pyodide.auto helper = axllm::agent("question:string -> answer:string");
auto out = helper.forward(llm, { {"question", "How should I proceed?"} });axllm::agent, axllm::AxAgentaxllm::ProcessCodeRuntime, axllm::RuntimeCapabilities, axllm::RuntimeEnvelope, javascript-quickjs, python-pyodideaxllm::optimize, axllm::playbook, axllm::AxPlaybook, axllm::AxBootstrapFewShot, axllm::AxGEPA, axllm::OptimizerEngine, axllm::OptimizerEvaluatorprovider-api examples only when the user explicitly has provider credentials available.no-key examples for deterministic local checks and provider request mapping.tools/*/skills/ into user packages.If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.