An automated utility for extracting specific video frames, time-stamped screenshots, and short segments from video files.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install video-extractor-pro
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 video-extractor-pro 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 Video Frames?
Video Frames is a specialized tool within the Openclaw Skills ecosystem designed to streamline the extraction of visual assets from video content. Whether you need a single snapshot from a specific timestamp or a series of frames for scene analysis, this tool provides the precision and automation required for professional media workflows. It bridges the gap between raw video data and actionable visual intelligence by providing a direct interface for AI agents to interact with video files.
By integrating this tool into your environment, you gain the ability to generate thumbnails, create GIF previews, and perform batch scene extraction. As part of the Openclaw Skills library, it is optimized for high performance and reliability, ensuring that developers can focus on building sophisticated media processing pipelines without worrying about the underlying complexities of video codec handling.
Video Frames Use Cases
- Creating high-quality thumbnails for video content management systems.
- Extracting specific frames for manual or AI-driven content moderation and review.
- Generating short GIF highlights for social media or documentation previews.
- Batch harvesting scene transitions to build training datasets for visual AI models.
- Isolating important moments from long-form recordings for archival purposes.
How Video Frames Works
- Provide the input video file path to the AI agent using the Openclaw Skills interface.
- Define the extraction parameters, such as specific timestamps, time ranges, or periodic intervals.
- The tool executes precise frame seeking to capture the visual data at the requested locations.
- Extracted images or video segments are processed and converted into the desired output format (JPG, PNG, or GIF).
- The resulting files are saved to a structured output directory for immediate access and further processing.
Video Frames Setup
To get started with this tool, ensure you have your agent environment configured to recognize Openclaw Skills. Install the package using the following command:
openclaw install video-frames
Ensure that system dependencies like ffmpeg are available on your path, as this tool leverages standard media libraries for high-fidelity extraction. Once installed, the agent will have immediate access to the extraction triggers.
Video Frames Data Schema & Taxonomy
The tool organizes extracted data based on the following metadata structure:
| Attribute | Description | Format |
|---|---|---|
| source_file | The path to the original video processed | String |
| timestamp | The exact time in the video where the frame was taken | HH:MM:SS.ms |
| output_type | The file format of the extracted asset | jpg / png / gif |
| frame_index | The sequential number of the frame in a batch process | Integer |
| storage_path | The destination path for the extracted media | String |
Video Frames Advanced Features
- Scene-based extraction that automatically identifies key transitions in the video content.
- Interval-based batch processing to create visual summaries of long-form media.
- Custom output templates that allow users to define specific naming conventions for extracted frames.
- Support for multi-agent workflows where one agent identifies key moments and this tool handles the extraction.
- High-speed GIF generation with optimized color palettes for web use.
SKILL.md
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