A high-performance utility for extracting specific frames or thumbnails from video files using ffmpeg integration.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install video-frames-extractor
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-frames-extractor 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 (ffmpeg)?
The video-frames skill provides a streamlined interface for AI agents and developers to interact with ffmpeg for visual data extraction. By leveraging this Openclaw Skills contribution, users can programmatically capture static imagery from any point in a video timeline, facilitating easier inspection and processing of media assets.
This tool is designed to bridge the gap between raw video files and actionable image data, making it an essential component for workflows that require visual verification or automated thumbnail generation. It ensures that Openclaw Skills can handle media-heavy tasks with precision and speed.
Video Frames (ffmpeg) Use Cases
- Generating high-quality thumbnails for video galleries or previews.
- Capturing specific UI frames for documentation and bug reporting.
- Inspecting video content at precise timestamps for visual verification.
- Extracting crisp PNG frames for design analysis or JPGs for quick social sharing.
How Video Frames (ffmpeg) Works
- The skill receives a file path to a target video and optional parameters like timestamp and output destination.
- It verifies the presence of the ffmpeg binary within the environment.
- The shell script executes the optimized ffmpeg command to seek to the specified time and capture the frame.
- The resulting image is saved to the designated output path in the requested format (JPG or PNG).
- The agent or user receives the path to the extracted frame for further processing.
Video Frames (ffmpeg) Setup
To use this within the Openclaw Skills ecosystem, ensure ffmpeg is installed on your system.
On macOS using Homebrew:
brew install ffmpeg
Basic usage to extract the first frame:
./scripts/frame.sh /path/to/video.mp4 --out /tmp/frame.jpg
Extracting a frame at a specific timestamp:
./scripts/frame.sh /path/to/video.mp4 --time 00:00:10 --out /tmp/frame-10s.jpg
Video Frames (ffmpeg) Data Schema & Taxonomy
The video-frames skill follows a strict input/output pattern to ensure compatibility within Openclaw Skills workflows:
| Parameter | Type | Description |
|---|---|---|
input_path |
File Path | The source video file (e.g., .mp4, .mkv). |
--time |
String | The timestamp in HH:MM:SS format (default: start). |
--out |
File Path | The destination for the extracted image. |
Output files are typically generated as .jpg for compressed web use or .png for lossless quality.
Video Frames (ffmpeg) Advanced Features
- Direct binary dependency management for Openclaw Skills via brew integration.
- Precision seeking using the --time flag to answer 'what is happening' at specific intervals.
- Support for multiple image formats including PNG for high-fidelity UI extraction.
- Lightweight shell execution designed for low-overhead AI agent operations.
SKILL.md
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