An AI-powered tool that transforms markdown documents into structured, 1080p presentation videos and social content in minutes.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install markdown-editor
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install markdown-editor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
This skill allows developers and technical writers to bridge the gap between documentation and video production by automating the creation of visual content. By leveraging remote GPU nodes, it processes markdown files containing headers and bullet points to generate formatted video slides, complete with transitions and narration. It eliminates the need for manual timeline editing or complex export settings, providing a streamlined path from text to media.
Using Openclaw Skills like this one, users can automate the conversion of technical outlines into polished MP4 exports without installing heavy video editing software. The system manages session state and cloud rendering pipelines to ensure that high-quality video content is accessible directly through a simple text-based interface or API integration, making it ideal for rapid content creation.
To get started, ensure your environment is configured for the cloud rendering API. If you do not have a token, the skill can automatically generate an anonymous one for you during your first interaction.
# Set your API token as an environment variable to authenticate
export NEMO_TOKEN="your_token_here"
The skill automatically creates a session by sending a POST request to the project endpoint. It uses a UUID as a client identifier to manage your credit balance and tracks session states in ~/.config/nemovideo/ for persistence across prompts.
The skill organizes data through a session-based state mapping various tracks and media types to a timeline. It utilizes the following schema for managing video assets:
| Field | Description |
|---|---|
| t | Tracks representing Video, Audio, or Text layers |
| tt | Track Type identifier (0: Video, 1: Audio, 7: Text) |
| sg | Segments containing specific media timing, duration, and content data |
| m | Metadata including resolution, framerate, and export settings |
All session data and temporary assets are managed via unique session IDs, allowing Openclaw Skills to perform iterative editing without requiring local storage overhead.
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