An open-source AI video generation skill that transforms text descriptions into professional 1080p MP4 clips using cloud-based GPU rendering.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install text-to-video-open-source
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 text-to-video-open-source using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Text to Video Open Source is a developer-centric skill designed to bridge the gap between creative writing and video production. By integrating this skill into your AI agent workflow, you can generate cinematic sequences—such as a fox running through a snowy forest at dusk—directly from natural language prompts. This tool is a standout feature within the Openclaw Skills library, offering indie creators and developers a way to bypass expensive API subscriptions and complex local hardware requirements.
The skill operates by communicating with a high-performance cloud render pipeline. It handles the entire lifecycle of video creation, from interpreting scene descriptions to compositing layers and exporting final files in industry-standard formats like H.264 MP4. Whether you are building automated content pipelines or enhancing an AI coding assistant, this skill provides the necessary infrastructure for rapid, text-driven visual storytelling.
To get started with this component of the Openclaw Skills library, configure your environment and connect to the rendering API.
# Set your authentication token (optional but recommended)
export NEMO_TOKEN="your_nemo_api_token_here"
# The skill also supports anonymous sessions for testing
# Config files are typically stored in:
# ~/.config/nemovideo/
Ensure your AI agent has the appropriate headers configured for API attribution, including X-Skill-Source: text-to-video-open-source.
The skill organizes video projects using a structured draft schema. Below is the mapping for metadata and timeline organization:
| Key | Definition | Details |
|---|---|---|
session_id |
Project Identifier | Required for all stateful API calls |
t |
Tracks | Array of media layers (Video, Audio, Text) |
tt |
Track Type | 0 = Video, 1 = Audio, 7 = Text |
sg |
Segments | Specific clips or blocks within a track |
d |
Duration | Length of the segment in milliseconds |
m |
Metadata | Contains scaling, positioning, and file info |
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