A cloud-powered AI skill that replaces video backgrounds instantly using simple natural language descriptions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install editor-background-changer
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 editor-background-changer 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 Editor Background Changer?
Editor Background Changer is a professional-grade video editing tool designed for Openclaw Skills that eliminates the need for complex software or green screens. By leveraging remote GPU nodes, it allows users to upload video files and describe their desired environment—such as a clean studio or a professional office—and receive a rendered 1080p MP4 in under a minute.
This skill is specifically optimized for content creators, YouTubers, and remote presenters who require high-fidelity background swaps. It handles the entire render pipeline server-side, ensuring that even users with limited local hardware can produce high-quality video content with perfect subject-background contrast.
Editor Background Changer Use Cases
- Replacing messy home office backgrounds with professional studio backdrops for corporate presentations.
- Batch processing multiple video clips to maintain a consistent visual style across a social media campaign.
- Creating clean YouTube talking-head videos without the requirement of a physical green screen setup.
- Iterative video editing where users refine backgrounds and overlays through conversational AI prompts.
How Editor Background Changer Works
- Authentication: The skill checks for a NEMO_TOKEN or automatically generates an anonymous session via a UUID client identifier.
- Session Initialization: A dedicated project session is created to track the timeline, media metadata, and render tasks.
- Media Upload: Users provide video files (MP4, MOV, AVI, WebM) up to 500MB via multipart upload or direct URL.
- Intent Processing: Natural language instructions like "replace my office background with a clean studio backdrop" are processed via an SSE (Server-Sent Events) stream.
- Cloud Rendering: The instructions trigger a cloud GPU node to composite layers and apply H.264 compression.
- Export & Delivery: The skill polls the render status and provides a high-quality download URL once completion is confirmed.
Editor Background Changer Setup
To get started with this skill, ensure your environment is configured correctly:
# Set your API token as an environment variable
export NEMO_TOKEN="your_token_here"
# The skill will automatically manage session IDs and connection headers
# for the Openclaw Skills ecosystem.
If you do not have a token, the skill will perform a POST request to [https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token](https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token) to acquire 100 free credits.
Editor Background Changer Data Schema & Taxonomy
The skill organizes video projects using a structured session state and timeline draft system:
| Key | Description |
|---|---|
tracks |
Array of media layers (Video, Audio, or Text) |
video_infos |
Metadata including resolution, bitrate, and duration |
generated_media |
History of AI-generated assets and background swaps |
draft |
The JSON representation of the current timeline state |
Data is processed using short-key JSON (e.g., tt for track type and sg for segments) to ensure low-latency communication during SSE streams.
Editor Background Changer Advanced Features
- Multi-Agent Messaging Support: Integrates seamlessly within the Openclaw Skills framework for automated video processing workflows.
- SSE Heartbeat Management: Automatic handling of long-running GPU render tasks with status updates every 2 minutes.
- Iterative Timeline Editing: Maintains state across multiple prompts, allowing for non-destructive editing and layering.
- Platform-Specific Optimization: Auto-detects the host platform (Clawhub, Cursor, etc.) to apply optimized header attribution.
SKILL.md
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