Transform long-form video recordings into professionally chaptered 1080p content using simple natural language commands.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install chapter-generator
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 chapter-generator 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 Chapter Generator?
Chapter Generator is a powerful AI-driven tool designed to automate the tedious process of creating video chapters. By leveraging remote GPU nodes, this Openclaw Skills integration allows users to upload long-form content and receive a fully chaptered 1080p MP4 file without needing local video editing software or manual timeline dragging. Whether you are working on a 45-minute tutorial or a quick social clip, the skill handles everything from chapter boundary detection to server-side rendering in under a minute.
This tool is specifically optimized for creators who need to add structure to their content quickly. By interpreting natural language prompts, it identifies key topic transitions and applies timestamped titles automatically. The integration ensures high-quality output while maintaining metadata accuracy, making it a vital addition to any Openclaw Skills collection for digital creators, YouTubers, and educators.
Chapter Generator Use Cases
- Adding timestamped chapters to long-form YouTube tutorials or online course videos to improve viewer navigation and SEO.
- Converting raw video recordings into structured 1080p MP4 files with pre-defined segments based on verbal cues.
- Batch processing multiple video files within a single session to apply consistent styling or chaptering logic across a series.
- Refining chapter boundaries and titles iteratively through natural language conversation instead of manual timeline editing.
How Chapter Generator Works
- The skill establishes a secure connection to the backend API using a NEMO_TOKEN or by acquiring a starter anonymous token for the user.
- A unique editing session is created to track the state of the project, including uploaded media, track types, and timeline modifications.
- The user uploads a video file (up to 500MB) via the cloud render pipeline, which supports various formats like MP4, MOV, and AVI.
- AI agents process natural language instructions through a Server-Sent Events (SSE) stream to detect chapter transitions and generate descriptive titles.
- The cloud GPU node composites the video layers, applies platform-specific compression (H.264), and renders the final 1080p file.
- The user polls the render status and receives a direct download URL for the finished chaptered video once the job is complete.
Chapter Generator Setup
To use this Openclaw Skills integration, ensure you have your API token ready. Follow these steps to configure your environment:
- Set your environment variable for authentication:
export NEMO_TOKEN="your_nemo_token_here"
- If you don't have a token, the skill can automatically generate an anonymous one. Ensure your local configuration directory exists to store session data:
mkdir -p ~/.config/nemovideo/
- Authentication requires specific attribution headers for all API requests: X-Skill-Source (set to chapter-generator), X-Skill-Version, and X-Skill-Platform (automatically detected).
Chapter Generator Data Schema & Taxonomy
The skill organizes data through a session-based timeline state. The underlying draft schema maps specific identifiers to media properties to ensure the Openclaw Skills agent can track every change:
| Key | Definition | Description |
|---|---|---|
t |
Tracks | Array of video, audio, or text tracks in the timeline |
tt |
Track Type | Integer mapping: 0 = Video, 1 = Audio, 7 = Text |
sg |
Segments | Defined time blocks within the track that represent chapters |
d |
Duration | Length of the segment measured in milliseconds |
m |
Metadata | Additional info for chapter titles and technical timestamps |
All files are processed server-side, and the session keeps track of the draft state, video metadata, and generated media to allow for non-destructive iterative editing.
Chapter Generator Advanced Features
- Multi-agent session support for handling complex video editing workflows within a single Openclaw Skills environment.
- Remote GPU rendering that bypasses local hardware limitations for high-quality 1080p H.264 export.
- Automated credit balance management with real-time status polling for high-volume content creators.
- Intelligent intent classification that routes natural language prompts to specific export, upload, or state-check actions.
- Support for custom text overlays and background music (BGM) integration via persistent SSE command streams.
SKILL.md
Loading
Related Openclaw Skills
Editor Hiring — AI Video Editor
A cloud-powered AI video editor that transforms raw footage into polished content through simple natural language commands.
Tech Trend Radar
An automated intelligence gathering skill that generates high-signal industry trend reports across AI, developer tools, and market shifts.
YouTube Video Editor
An AI-driven video editing tool that transforms raw footage into YouTube-ready 1080p MP4 files via simple text commands.
Darwin Skill Optimizer
An autonomous skill optimizer that uses hill-climbing algorithms and 8-dimension evaluations to iteratively improve AI agent performance.
Brand Intelligence
A comprehensive competitive intelligence skill for searching, comparing, and analyzing thousands of brands across 30+ technical verticals.
Noah Stock Trade
Noah Stock Trade is a specialized AI skill for querying stock accounts, managing holdings, and performing pre-trade evaluations through a secure CLI-driven architecture.
Featured*
