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Auto Video Cut
作者
zhuchenggong19851114-design
· GitHub ↗
· v1.0.0
· MIT-0
90
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当前安装
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版本数
在 OpenClaw 中安装
/install auto-video-cut
功能描述
Automatically trims single-speaker videos by detecting and removing silence and filler to produce a rough cut with quality scoring and deduplication.
使用说明 (SKILL.md)
auto-video-cut
抖音/视频自动剪辑Skill - 自动识别视频中的废话、沉默片段，生成粗剪版本。
适用场景
- ✅ 单人出镜视频（vlog、教程、播客、知识分享）
- ❌ 多人对话、采访
- ❌ 音乐/B-roll较多的内容
功能
- 场景A - 单视频：自动从单个视频中选取最佳片段
- 场景B - 批量处理：处理多个视频，跨视频去重，拼接成片
- 智能评分：4维度评分（清晰开始/结束、流畅度、自然节奏）
- 内容去重：基于语音文本的相似度检测
- 自动报告：生成详细的处理报告
前置要求
- Python 3.8+
- FFmpeg（包含ffprobe）
- openai-whipser
安装依赖
# macOS
brew install ffmpeg
pip install openai-whisper
# Ubuntu / Debian
sudo apt install ffmpeg
pip install openai-whisper
# Windows
# 下载 FFmpeg: https://ffmpeg.org/download.html
# 添加到 PATH
pip install openai-whisper
使用方法
场景A：单视频剪辑
python3 video_editor_auto.py /path/to/video.mp4 ./output
场景B：批量处理+去重+拼接
python3 video_editor_auto.py /path/to/videos_folder ./output
输出
*.mp4- 剪辑后的视频*_报告.md- 处理报告
参数配置
在脚本顶部的 CONFIG 字典中修改：
| 参数 | 说明 | 默认值 |
|---|---|---|
| silence_noise | 静音检测阈值(dB)，越低越严格 | -30 |
| silence_duration | 最小静音时长(秒) | 0.8 |
| min_score | 最低评分(0-100) | 90 |
| min_duration | 最短片段时长(秒) | 15 |
| crf | 视频质量(18=无损) | 18 |
调优建议
- 环境嘈杂 → silence_noise 设为 -35
- 片段太碎 → silence_duration 设为 1.0
- 想保留更多候选 → min_score 设为 85
工作流程
拍摄素材 → 归档到文件夹 → 运行脚本 → AI分析+剪辑 → 输 出粗剪 → 剪映精修 → 完成
来源
基于 gilbertwuu/Auto-Cut-video-A-Roll 项目改编
安全使用建议
This skill appears to do what it says: it uses FFmpeg to detect silence and OpenAI Whisper to transcribe, then scores and trims segments. Before installing/running: (1) fix the filename mismatch in the README or call the provided script (video_editor_auto_v4.6.py). (2) Ensure FFmpeg is installed and on PATH. (3) Be aware Whisper may download model weights the first time (it will use network and disk cache). (4) The script runs locally and reads/writes files in the work/output folders you supply — review those outputs and the script if you want to confirm no unintended file access. (5) If you will run this on sensitive videos, test on non-sensitive material first and review the transcript files it generates. If you want, I can point out exact lines to change for the filename or help inspect the remainder of the source for further hardening.
功能分析
Type: OpenClaw Skill
Name: auto-video-cut
Version: 1.0.0
The skill bundle is a legitimate video editing tool designed to automate the process of cutting silence and 'filler' content from videos. The main script, video_editor_auto_v4.6.py, uses FFmpeg and OpenAI Whisper to perform silence detection, transcription, and fluency analysis. It employs subprocess.run with argument lists to safely execute external commands without shell injection risks. The logic is consistent with the stated purpose in SKILL.md, and there is no evidence of data exfiltration, malicious persistence, or prompt injection.
能力评估
Purpose & Capability
The name/description (auto-trim single-speaker video, silence/filler removal, dedup, scoring) aligns with the code and SKILL.md. The script uses FFmpeg for audio/video processing and invokes Whisper for transcription, which is exactly what this functionality requires. Sample work files included are consistent with expected inputs/outputs.
Instruction Scope
SKILL.md instructs the agent/user to run `python3 video_editor_auto.py` but the repository contains `video_editor_auto_v4.6.py` (filename mismatch) — you'll need to run the actual filename or rename it. The instructions and script operate only on supplied video files and a local work directory; they do not reference or require any unrelated system paths or credentials. Note: running Whisper may download model weights (network access) on first run; the SKILL.md does not explicitly warn about model downloads.
Install Mechanism
There is no install spec; dependencies are installed via normal package managers (pip/brew) as documented. requirements.txt only lists openai-whisper. No remote arbitrary archive downloads or installers are present in the manifest. The only external tooling invoked is FFmpeg and the Whisper package.
Credentials
The skill declares no required environment variables, credentials, or config paths and the code does not attempt to read secrets or unrelated env vars. All runtime needs (ffmpeg, whisper) are proportional to the stated purpose.
Persistence & Privilege
always:false and no install-time or runtime behavior attempts to persist the skill into system-wide agent settings. The script writes output and temporary files to the provided work/output directories only.
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 auto-video-cut - 安装完成后，直接呼叫该 Skill 的名称或使用
/auto-video-cut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
v1.0.0
auto-video-cut 1.0.0
- 初始发布，支持抖音/单人视频的自动剪辑。
- 自动识别并剪除废话、沉默片段，生成粗剪版本。
- 单视频自动选段、批量处理与跨视频去重拼接。
- 提供4维智能评分与基于文本的内容去重。
- 脚本参数可自定义，自动生成剪辑报告。
- 依赖 Python 3.8+、FFmpeg、openai-whisper。
元数据
常见问题
Auto Video Cut 是什么？
Automatically trims single-speaker videos by detecting and removing silence and filler to produce a rough cut with quality scoring and deduplication. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 90 次。
如何安装 Auto Video Cut？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install auto-video-cut」即可一键安装，无需额外配置。
Auto Video Cut 是免费的吗？
是的，Auto Video Cut 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Auto Video Cut 支持哪些平台？
Auto Video Cut 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 Auto Video Cut？
由 zhuchenggong19851114-design（@zhuchenggong19851114-design）开发并维护，当前版本 v1.0.0。
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