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在 OpenClaw 中安装
/install pedestrian-traffic-counting-video-frame-extraction
功能描述
Extract frames from video files and save them as images using OpenCV
安全使用建议
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.
功能分析
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.
能力评估
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.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install pedestrian-traffic-counting-video-frame-extraction - 安装完成后，直接呼叫该 Skill 的名称或使用
/pedestrian-traffic-counting-video-frame-extraction触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v0.1.0
Bulk publish from all-task-skills-dedup
元数据
常见问题
video-frame-extraction 是什么？
Extract frames from video files and save them as images using OpenCV. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 78 次。
如何安装 video-frame-extraction？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install pedestrian-traffic-counting-video-frame-extraction」即可一键安装，无需额外配置。
video-frame-extraction 是免费的吗？
是的，video-frame-extraction 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
video-frame-extraction 支持哪些平台？
video-frame-extraction 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 video-frame-extraction？
由 lnj22（@lnj22）开发并维护，当前版本 v0.1.0。
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