A powerful AI-driven video editor that allows you to transform raw footage into polished content by simply editing the transcript or providing text instructions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-video-editor-descript
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 ai-video-editor-descript 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 AI Video Editor Descript?
AI Video Editor Descript is a specialized tool designed to simplify video production by leveraging a cloud rendering pipeline. It allows creators to perform complex editing tasks—such as trimming silences, removing filler words, and adding captions—using only natural language or transcript-based edits. By integrating this capability through Openclaw Skills, developers and content creators can bypass traditional video editing software and generate high-quality 1080p MP4 exports through a streamlined API-driven workflow.
The skill handles the heavy lifting of video processing by offloading tasks to cloud GPU nodes. This ensures that even high-resolution files up to 500MB are processed efficiently, allowing for rapid iteration and deployment of video content across various platforms. Whether you are producing podcasts, social media clips, or tutorials, this skill provides a text-first approach to video manipulation.
AI Video Editor Descript Use Cases
- Automatically remove filler words like 'um' and 'ah' from long-form interview recordings.
- Generate social media-ready clips with automatic captions and text overlays for better engagement.
- Rapidly trim silences and dead air from raw footage to create tighter, more professional edits.
- Batch process multiple video assets with consistent styles and background music in a single session.
How AI Video Editor Descript Works
- Authentication is established by setting a NEMO_TOKEN or generating an anonymous session token via the API.
- A project session is initiated to maintain the state of the video timeline and media metadata.
- Raw video footage is uploaded to the cloud rendering pipeline, supporting formats like MP4, MOV, and WebM.
- Natural language instructions are sent via a Server-Sent Events (SSE) stream to trigger transcript-based editing actions.
- The project state is updated in real-time, mapping video, audio, and text segments to a structured timeline schema.
- A render job is queued on a cloud GPU node to composite the layers and apply platform-specific compression.
- The skill polls the render status every 30 seconds until a final 1080p MP4 download URL is provided.
AI Video Editor Descript Setup
To integrate this capability into your workflow using Openclaw Skills, you must configure the necessary environment variables and paths.
# Set the primary environment variable for API access
export NEMO_TOKEN="your_nemo_api_token"
# The skill utilizes the following configuration path
# ~/.config/nemovideo/
On the first interaction, the skill will automatically verify the token or generate a UUID-based anonymous token with 100 credits if no token is provided.
AI Video Editor Descript Data Schema & Taxonomy
The skill manages video projects using a specific draft mapping system to organize the timeline and assets:
| Key | Name | Description |
|---|---|---|
t |
Tracks | An array of all media tracks (Video, Audio, Text). |
tt |
Track Type | Identifies the content type (0=video, 1=audio, 7=text). |
sg |
Segments | Defines specific time-coded sections within a track. |
d |
Duration | The length of a segment measured in milliseconds. |
m |
Metadata | Technical details including file info and asset properties. |
AI Video Editor Descript Advanced Features
- Smart Filler Word Detection: Automatically identifies and removes vocal disfluencies through transcript analysis.
- Automated Captioning: Generates and syncs text overlays based on the audio track content.
- Persistent Session State: Maintains the timeline draft across multiple interactions, allowing for iterative refinement.
- Cloud GPU Composite: Uses high-performance remote nodes for H.264 video encoding and layer compositing.
- SSE-Driven Logic: Employs Server-Sent Events for real-time feedback during complex AI editing operations.
SKILL.md
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