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Install in OpenClaw
/install pedestrian-traffic-counting-video-frame-extraction
Description
Extract frames from video files and save them as images using OpenCV
Usage Guidance
This skill appears coherent and focused on extracting frames with OpenCV. Before installing or running it, ensure the agent environment has Python and OpenCV (cv2) available (the skill has no install step). Be aware it will read any video file path you provide and write potentially large numbers of image files — check disk space and run in a controlled output directory to avoid accidental overwrites. If you do not want the agent to access arbitrary local files, limit its filesystem permissions or only supply explicit input file paths. If you need higher assurance, request the full SKILL.md (untruncated) and confirm it does not include any hidden network calls or commands beyond what was supplied here.
Capability Analysis
Type: OpenClaw Skill
Name: pedestrian-traffic-counting-video-frame-extraction
Version: 0.1.0
The skill bundle provides standard instructions and Python code snippets for extracting frames from video files using the OpenCV library. The code examples in SKILL.md follow best practices for video processing, including metadata retrieval, error handling, and resource management (cap.release), with no evidence of malicious intent, data exfiltration, or prompt injection.
Capability Assessment
Purpose & Capability
Name, description, and SKILL.md all describe frame extraction using OpenCV and the required operations (reading video files, writing image files). There are no unexplained credentials, binaries, or config paths requested.
Instruction Scope
Instructions and code examples are narrowly scoped to opening a video file, reading frames, saving images, and producing a JSON summary. They do not reference unrelated system files, environment variables, or external endpoints.
Install Mechanism
This is an instruction-only skill with no install spec and no code files to install; that minimizes risk. It does require the runtime to provide OpenCV (cv2) and Python, but the skill itself does not perform any downloads or installs.
Credentials
No environment variables, credentials, or config paths are requested. File I/O (reading video, writing frames) is necessary and proportionate to the stated task.
Persistence & Privilege
The skill is not marked always:true and is user-invocable; it does not request persistent system presence or modify other skills or system-wide settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install pedestrian-traffic-counting-video-frame-extraction - After installation, invoke the skill by name or use
/pedestrian-traffic-counting-video-frame-extraction - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Bulk publish from all-task-skills-dedup
Metadata
Frequently Asked Questions
What is video-frame-extraction?
Extract frames from video files and save them as images using OpenCV. It is an AI Agent Skill for Claude Code / OpenClaw, with 78 downloads so far.
How do I install video-frame-extraction?
Run "/install pedestrian-traffic-counting-video-frame-extraction" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is video-frame-extraction free?
Yes, video-frame-extraction is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does video-frame-extraction support?
video-frame-extraction is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created video-frame-extraction?
It is built and maintained by lnj22 (@lnj22); the current version is v0.1.0.
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