Medeo Video Skill releases OpenClaw chat-to-video setup with 30-second API-key install

• Medeo Video Skill has launched an OpenClaw setup that turns a plain-language prompt into a finished video link, with the whole job running behind the scenes instead of through a separate editor, according to launch thread.
• The install flow is unusually short: the install demo says users can ask OpenClaw to install the skill from the GitHub repo, then complete Medeo API-key setup in about 30 seconds.
• The feature set goes beyond one-shot prompting. In feature list, the creator says you can bring your own images or clips, queue recurring daily videos, and get notified when asynchronous renders finish.
• The project is also open source under MIT, with the repo post pointing to a public GitHub release for the OpenClaw integration.

The release is not a standalone video app. It is an OpenClaw skill that lets an AI assistant handle Medeo video generation through chat, so the workflow starts with a text request like a coffee-brewing video and ends with a delivered link rather than a dashboard session. The repo post frames that as “text in, video link out” on a five-to-10-minute turnaround.

That matters for creative teams because the handoff is the product: prompt, render, and delivery sit inside the assistant instead of being split across upload screens, export dialogs, and revision loops.

The setup starts by sending OpenClaw a natural-language install command plus the repo reference at the GitHub repo. From there, the assistant walks through Medeo API-key setup and stores the configuration locally, according to the repo summary attached to the install post.

Once connected, the skill supports several production paths. The feature list says users can generate a ready-to-post video from one sentence, upload their own images or footage as source assets, and schedule recurring outputs while renders run asynchronously in the background.

The GitHub release at the public repo makes this more than a demo thread. Its attached summary describes template support, job tracking, history management, and controls for parameters such as orientation or length.

The same summary also notes a practical constraint: generation uses Medeo credits, so this is open-source orchestration around a paid rendering backend rather than a fully local video stack.