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Use when setting up an autonomous ML experimentation harness (an "autoresearch" loop) — a fixed harness that owns data + metrics plus a hackable training script an LLM iterates on under a fixed time budget. Use when scaffolding harness.py/train.py/program.md, designing structured training-dynamics logging for agents to read, or enforcing that experiments cannot game the metric.