dsh-video-to-notes

skilltested: passnpmMIT

Turns course, lecture, tutorial, meeting, and talk videos into structured study notes: it extracts the audio track with ffmpeg, transcribes it with Whisper, then writes notes with a chapter outline, emphasis markers, and a quick-reference card.

下载量 / Downloads
789
依赖体积 / node_modules
0.04 MB
测试时间 / Tested
2026-11-07
DSH 版本 / Version
0.2.2-rc.1

Install

dsh plugin --profile web add dsh-video-to-notes

Sandbox test results

StageResult
1 install✓
2 list✓
3 mount✓
4 boot—

Four stages run in an isolated sandbox: install (network on) → list → mount → boot (last three with no network).

README

dsh-video-to-notes

Turn course, lecture, tutorial, documentary, meeting, and talk videos into structured study notes, inside DeepSeek Harness.

将视频(课程 / 讲座 / 教程 / 纪录片 / 会议 / 演讲等)自动转为高质量结构化学习笔记的 DSH 技能包。

看视频 ≠ 学会。笔记才是真正属于你的知识。

Install

dsh plugin --profile web add dsh-video-to-notes

Restart DSH afterwards. The bundle applies one patch row and changes nothing else.

What the bundle does

This package ships no runtime plugin logic. Its substance is a single Skill:

skills/video-to-notes/
├── SKILL.md                  skill instructions and routing description
├── scripts/transcribe.py     ffmpeg + Whisper speech-to-text
├── scripts/download_video.py yt-dlp network download
└── references/               note templates and the detailed workflow

cordis.patch.yml inserts one @deepseek-ai/dsh-skill-filesystem row that mounts the packaged skills/ directory as an isolated provider (includeDefaultRoots: false), so this bundle contributes the video-to-notes skill without touching the project or user skill roots. The skill root resolves from the profile's own module resolution — the installed npm identity — never from a path concatenated onto baseUrl.

Requirements

The skill drives local tools; DSH does not install them for you.

Tool · Role · Install

python3 · runs the bundled scripts · brew install python3

ffmpeg / ffprobe · audio extraction, silence trimming, speed change · brew install ffmpeg

openai-whisper · speech recognition · pip3 install openai-whisper

yt-dlp · optional, only for video URLs · pip3 install yt-dlp

The skill instructs the agent to detect missing dependencies, name them, and wait for your explicit confirmation before installing anything.

What the skill does

1. Detect dependencies — reports exactly what is missing and asks before installing.

2. Acquire the video — a local path, or a URL downloaded with yt-dlp after you confirm the output directory.

3. Transcribe — Whisper with per-scenario defaults (base for ordinary videos, turbo for long ones, --language zh for Chinese, optional --strip-silence and --speed acceleration).

4. Write the notes — semantic chunking into a chapter outline, an optional Mermaid knowledge map for long content, ⭐/🔧/⚠️ emphasis markers, a closing quick-reference card, and a style matched to the content type (technical tutorial, classroom, talk, documentary).

Model choice, device selection (CUDA / Apple MPS / CPU), speed, and the note format are all decided by the skill; you only supply the video and any preferences.

Privacy and copyright

Transcripts and notes can contain sensitive material — review and delete them when they are no longer needed. Downloading third-party video must respect the source platform's terms; use it for personal study.

License

MIT

Rendered from the README published on npm. Formatted only, not edited.

Versions

Published on npm::1,最后更新 2026-09-21

Links

GitHub · Homepage · npm

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