Improvement Learner

What to consider before installing/running: - The skill appears to do what it says (evaluate and auto-improve SKILL.md), but the Python scripts import external modules (lib.common, lib.pareto) that are not included; running may fail or silently import code from an unexpected repo root. Verify those dependencies exist and inspect them. - The script will call a local 'claude' CLI via subprocess.run when available. If you have a 'claude' binary configured, skill text may be sent through that client — treat SKILL.md and any files you point it at as potentially sent to that service. If you don't want that, run with the --mock flag or ensure 'claude' is not on PATH. - The tools write memory and report files to directories you specify (memory-dir, output); review and choose those paths to avoid exposing sensitive data. - Optional plotting requires matplotlib/numpy; tests expect a Python test runner. Run in a sandbox or isolated environment first to confirm behavior. - If you plan to let the agent invoke this autonomously, be aware the ability to call an external LLM client increases blast radius; consider restricting execution or reviewing the code paths that call subprocess.run. - To raise confidence to 'benign', provide the missing lib.* implementations or confirm they come from a trusted upstream, and validate that 'claude' usage is acceptable for your environment.