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