HarnessHarvester generates executable Python harnesses from natural language task descriptions, executes them in a sandboxed environment, reviews them with multi-faceted LLM judges, and repairs failures using branching strategies. It includes two autonomous modes: autolearn (continuous discovery loop) and autoimprove (iterative enhancement of existing harnesses). This concept is designed to be an offline first harness/scaffolding builder where you get the harness instead of some remote api.