A powerful AI video generation skill that converts text descriptions and scripts into professional 1080p HD video files using a cloud-based rendering pipeline.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install text-to-hd
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install text-to-hd using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Text to HD — Generate HD Video from Text?
Text to HD is a specialized skill designed for Openclaw Skills that bridges the gap between creative writing and video production. It allows developers and creators to turn a two-sentence scene description into high-definition 1080p video files without the need for manual timeline editing or complex export configurations. By leveraging a cloud GPU rendering pipeline, the skill processes natural language prompts to generate visually stunning content in approximately 1-2 minutes.
This skill is particularly effective for generating HD videos from written descriptions or scripts, providing an automated solution for content creators and marketers. It handles everything from asset uploading and scene composition to the final rendering of MP4 files, ensuring high-quality output with minimal technical overhead.
Text to HD — Generate HD Video from Text Use Cases
- Rapidly generating HD videos from written descriptions or scripts for social media content.
- Converting a two-sentence scene description into a 1080p MP4 for storyboarding or prototyping.
- Creating 30-second marketing clips from simple text scripts like 'A sunrise over a mountain lake'.
- Batch processing multiple video scenes within a single session for consistent stylistic output.
- Automated video editing and background music integration through natural language commands.
How Text to HD — Generate HD Video from Text Works
- The user provides a text prompt or script to the agent, which triggers the Openclaw Skills intent classification.
- The skill establishes a secure session with the Nemo Video cloud backend using a NEMO_TOKEN.
- Scene descriptions are sent via a Server-Sent Events (SSE) stream to the cloud GPU nodes for real-time processing.
- The cloud pipeline composites video layers, applies text overlays, and integrates audio tracks based on the instructions.
- A render job is queued to compress the video into H.264 format at 1080p resolution.
- The skill polls the rendering status every 30 seconds until the job is completed and a download URL is provided to the user.
Text to HD — Generate HD Video from Text Setup
To get started with this skill within the Openclaw Skills ecosystem, ensure your environment is configured:
# Set your API token for the cloud backend
export NEMO_TOKEN="your_token_here"
# The skill will automatically generate a Client ID and
# establish a session on first run.
If a token is not found, the skill will automatically attempt to acquire an anonymous token with 100 free credits to get you started immediately.
Text to HD — Generate HD Video from Text Data Schema & Taxonomy
The skill manages video projects using a session-based state. The data is organized as follows:
| Component | Description | Key Metadata |
|---|---|---|
| Tracks | Organized layers of media | tt (0: Video, 1: Audio, 7: Text) |
| Segments | Specific clips within a track | d (Duration in ms), sg (Segment ID) |
| Draft | The JSON representation of the timeline | t (Tracks array) |
| Output | Final rendered file metadata | format (MP4/MOV), quality (High) |
Supported file formats include MP4, MOV, AVI, WEBM, MKV, JPG, PNG, and MP3.
Text to HD — Generate HD Video from Text Advanced Features
- Multi-track timeline management for complex layering of video, audio, and text.
- Automated session persistence allowing for iterative editing and refinement of the same project.
- Intelligent mapping of GUI-based instructions (drag, drop, click) into backend API operations.
- Real-time credit balance monitoring and automatic token re-acquisition for uninterrupted workflows.
- Support for platform-specific headers to track skill usage across different IDEs like Cursor or Clawhub.
SKILL.md
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