name: "ax-python-refine" description: "Use when writing Python code with axllm for reward-scored generation, iterative candidate improvement, evaluator feedback, and optimizer-backed refinement patterns." version: "25.0.0"

Ax Refinement Patterns For Python

This skill helps an agent write Python 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

• Improve generated outputs with evaluator feedback or optimizer artifacts.
• Port TypeScript refinement intent into generated-language surfaces without assuming TypeScript-only helpers.
• Use generated optimizer APIs when the target package does not expose a standalone refine helper.

Package Facts

• Language: Python.
• 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

from axllm import AxGEPA
engine = AxGEPA(reflection_client)
result = engine.optimize(request, evaluator)

Relevant API Surface

• AxGen: ax, AxGen, run_control, AxRunControl, Callable[[str, dict | None], dict | None], set_caching_function
• Optimizers: optimize, playbook, AxPlaybook, AxBootstrapFewShot, AxGEPA, OptimizerEngine, 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.