How I Built an AI Video Editor as an OpenClaw Skill

Video editing is one of those things that feels fundamentally tied to a GUI. You drag clips, you scrub timelines, you click Export. The whole workflow is built around visual feedback. So when I set out to build nemo-video — an OpenClaw skill that lets you edit videos by chatting — the first question was: can an AI agent actually do this without a screen? Turns out yes. But not without a few interesting problems to solve. The Core Problem: A Backend That Thinks It Has a GUI NemoVideo's backend AI agent was designed to work with a web interface. It would say things like: "Click the Export button to download your video" "Drag the clip to the timeline" "Check the dashboard for your remaining credits" None of these instructions make sense when you're talking to an AI assistant in a terminal or chat app. There's no button. There's no timeline to drag things to. This is the fundamental challenge: the backend doesn't know it's talking to an agent, not a human with a browser. My solution was to