A cloud-powered AI video editing skill for trimming, enhancing, and exporting high-quality MP4 files without local processing.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install edit-video
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 edit-video 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 Edit Video Skill?
The Edit Video skill is a sophisticated integration for AI agents that offloads heavy video processing to cloud GPUs. It allows developers and creators to manipulate raw video files—including MP4, MOV, and WebM—through simple natural language commands. By leveraging the Openclaw Skills framework, this tool handles the heavy lifting of video composition, layer management, and platform-specific compression.
Designed for speed and efficiency, the skill supports files up to 500MB and specializes in generating polished 1080p exports. Whether you are automating content creation or building a video-centric workflow, this skill provides a seamless bridge between raw assets and production-ready media through a robust SSE-based communication pipeline.
Edit Video Skill Use Cases
- Automating the removal of silent gaps in screen recordings or vlogs.
- Applying professional transitions and background music overlays to raw clips.
- Converting and compressing various video formats into standardized 1080p MP4 files.
- Batch processing multiple assets within a single AI-guided session.
- Rapidly iterating on video drafts using iterative natural language feedback.
How Edit Video Skill Works
- The user provides raw video footage or a URL which is uploaded to the cloud via the Openclaw Skills interface.
- An anonymous or authenticated NEMO_TOKEN is established to authorize requests and manage credit balances.
- A session is initialized to track the state of the video timeline, including tracks for video, audio, and text.
- Natural language instructions are sent via a Server-Sent Events (SSE) stream, where the backend interprets intent for trimming, enhancing, or adding effects.
- The cloud GPU node composites the video layers and renders the final file.
- The system polls the render status and provides a high-quality download URL once the export is complete.
Edit Video Skill Setup
To get started with this skill, ensure your environment is configured correctly:
# Set your API token
export NEMO_TOKEN="your_nemo_token_here"
# The skill will automatically check for configuration at:
# ~/.config/nemovideo/
If you do not have a token, the skill can automatically generate a 7-day anonymous token with 100 credits by POSTing to the auth endpoint with a unique X-Client-Id header.
Edit Video Skill Data Schema & Taxonomy
The skill manages video data using a structured timeline draft. The schema utilizes shorthand keys for optimized performance:
| Key | Description | Values |
|---|---|---|
t |
Tracks | Array of media layers |
tt |
Track Type | 0: Video, 1: Audio, 7: Text |
sg |
Segments | Specific clips within a track |
d |
Duration | Length in milliseconds |
m |
Metadata | Asset source and properties |
Exported files are delivered as 1080p MP4 by default, with support for source formats including AVI, WebM, and MOV.
Edit Video Skill Advanced Features
- Multi-layer compositing for simultaneous video, BGM, and text overlays.
- Automatic SSE stream heartbeats to maintain connection during long GPU render tasks.
- Persistent session state allowing users to refine edits without re-uploading assets.
- Intelligent intent classification for routing requests like aspect ratio changes or credit balance checks.
- Automatic attribution headers (X-Skill-Source) for tracking across different Openclaw Skills implementations.
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