dsh-video-to-notes
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.
Install
dsh plugin --profile web add dsh-video-to-notes
Sandbox test results
| Stage | Result |
|---|---|
| 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