← 返回 Skills 市场
murrayhoung

Video Analyzer CN

作者 Murrayhoung · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
115
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install video-analyzer-cn
功能描述
视频内容分析工具。支持B站、抖音、今日头条视频链接。 发送视频URL → 自动下载 → 抽帧 → 本地AI逐帧识别 → 综合总结。 使用本地minicpm-v模型,无需云端API。
安全使用建议
What to check before installing: - Correctness: SKILL.md refers to references/analyze.py but the provided script is scripts/analyze_frames.py — confirm filenames and paths so the agent will actually run the analyzer. - Local model: The analyzer sends base64 images to http://localhost:11434/api/generate (common Ollama default). Ensure you run and trust a local model server on that port before using the skill; otherwise the requests will fail or hit an unexpected service. - Browser automation: The skill asks the agent to extract video.src from pages using Chrome devtools (MCP). That requires the agent to interact with your browser; consider whether you trust the agent to access your open browser tabs and DOM. Prefer manually supplying the direct video URL if you are uncomfortable. - External services: The doc mentions an optional 'agent-reach' douyin MCP service. Avoid using any external MCP service unless you understand where data (video URLs or frames) will be sent — that could leak video content or metadata off your machine. - Test with non-sensitive content first: Run the skill on a short public video to confirm behavior, temp file locations, and that only localhost and the video hosts are contacted. - Clean up: Confirm the temporary workspace path and delete temp videos/frames after use (the docs describe cleanup but verify it runs). If the author provides corrected SKILL.md (pointing to the actual analyzer file) and clarifies that no external agent-reach service is required (or documents exactly when it's used and where it runs), this assessment could be upgraded to 'benign'.
能力评估
Purpose & Capability
The name/description match the included scripts: download (douyin_download.py) and per-frame analysis (analyze_frames.py) submitting base64 images to a local model API. Requested tools (ffmpeg, yt-dlp, Python, Chrome, local minicpm-v/ollama) are consistent with the stated workflow. Minor mismatch: SKILL.md refers to references/analyze.py but the repo has scripts/analyze_frames.py — likely a documentation vs file-layout inconsistency that will break automated runs unless corrected.
Instruction Scope
Instructions tell the agent to extract Douyin video URLs via browser devtools (Chrome MCP) and to possibly use an external 'agent-reach' douyin MCP service. Browser automation means the agent would interact with the user's browser DOM (potentially exposing pages/tokens) — this is sensitive. The skill also instructs manipulating the PATH in a PowerShell snippet and uses hard-coded local temp paths. All network calls in code target video hosts and localhost:11434 (a local model server), but the mention of an external agent-reach MCP is an out-of-band dependency that could route data off-device if used.
Install Mechanism
No install spec (instruction-only plus small Python scripts). Nothing in the manifest downloads or executes remote archives during install. Risk from install-time code is low.
Credentials
The skill requests no environment variables or credentials (good). However it uses hard-coded Windows paths (C:\Users\39535\.openclaw\workspace\tmp and D:\AI\ffmpeg), and assumes a local model API at http://localhost:11434 — these are plausible but user-specific assumptions. The browser-based extraction step could access browser state; SKILL.md explicitly warns not to use cookies-from-browser due to Chrome cookie encryption, but the agent still needs browser access to retrieve video.src. No secrets are requested by the skill itself.
Persistence & Privilege
always is false and there are no service/account modifications. The skill does not request permanent platform-level privileges. It writes temporary files to a workspace tmp path (documented) and expects the user/agent to clean them up.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install video-analyzer-cn
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-analyzer-cn 触发
  4. 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
v1.0.0
B站/抖音/今日头条视频内容分析,本地AI模型识别
元数据
Slug video-analyzer-cn
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Video Analyzer CN 是什么?

视频内容分析工具。支持B站、抖音、今日头条视频链接。 发送视频URL → 自动下载 → 抽帧 → 本地AI逐帧识别 → 综合总结。 使用本地minicpm-v模型,无需云端API。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 115 次。

如何安装 Video Analyzer CN?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install video-analyzer-cn」即可一键安装,无需额外配置。

Video Analyzer CN 是免费的吗?

是的,Video Analyzer CN 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Video Analyzer CN 支持哪些平台?

Video Analyzer CN 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 Analyzer CN?

由 Murrayhoung(@murrayhoung)开发并维护,当前版本 v1.0.0。

💬 留言讨论