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-clip-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-clip-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 is a technical utility designed for Openclaw Skills users who need to bridge the gap between video content and static image analysis. By leveraging the industry-standard ffmpeg engine, it allows AI agents and developers to programmatically capture high-quality stills from any point in a video timeline.
Whether you are building a visual inspection pipeline or simply need to generate quick thumbnails for UI previews, this skill provides a streamlined interface for media manipulation. It focuses on precision and speed, ensuring that even large video files can be sampled at specific timestamps without manual overhead.
Video Frames (ffmpeg) Use Cases
- Capturing UI frames for design inspection and documentation.
- Generating preview thumbnails for media galleries and video libraries.
- Sampling frames at specific timestamps to analyze visual content with AI models.
- Creating quick-share JPEG snapshots for team communication and bug reporting.
How Video Frames (ffmpeg) Works
- The skill receives a file path to a target video and optional parameters such as timestamp and output format.
- It invokes a shell script that interfaces with the local ffmpeg binary to process the request.
- ffmpeg seeks to the designated time (if provided) or defaults to the first frame of the stream.
- A single frame is decoded and encoded into the specified image format (JPG or PNG).
- The resulting file is saved to the designated output path for further use by the agent or user.
Video Frames (ffmpeg) Setup
To use this contribution to Openclaw Skills, you must have ffmpeg installed on your system. On macOS, you can use the following command:
brew install ffmpeg
Once the binary is available, you can execute the extraction script from your base directory:
./scripts/frame.sh /path/to/video.mp4 --time 00:00:10 --out /tmp/output.jpg
Video Frames (ffmpeg) Data Schema & Taxonomy
The skill manages data through direct file system operations with the following specifications:
| Input | Type | Description |
|---|---|---|
video_path |
File Path | The source video file (mp4, mkv, etc.) |
--time |
String | Timestamp in HH:MM:SS format |
--out |
File Path | Target path for the generated image |
Supported output formats include .jpg for optimized file size and .png for lossless quality.
Video Frames (ffmpeg) Advanced Features
- Precise seeking using the
--timeflag to capture specific events in a video stream. - Multi-format support, allowing users to toggle between JPEG for speed and PNG for high-fidelity UI captures.
- Integration-ready CLI architecture, making it easy to incorporate into larger Openclaw Skills automation workflows.
- Lightweight dependency management through the Openclaw metadata specification.
SKILL.md
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