Import To Obsidian

Import to Obsidian

Save any web content, video, or text into the Obsidian vault as a structured, tagged note with graph connections.

Vault Path

/Users/adam/Library/Mobile Documents/iCloud~md~obsidian/Documents/Tony

Folders: 前哨/, 中文教学/, 计算机科学/, 数学/, 高考/, 最新资讯/, 剪藏/

Workflow

digraph import {
  "Input" -> "Type?";
  "Type?" -> "URL" [label="URL"];
  "Type?" -> "Text" [label="raw text"];
  "URL" -> "Video?";
  "Video?" -> "yt-dlp subs" [label="YouTube/B站"];
  "Video?" -> "defuddle" [label="web page"];
  "yt-dlp subs" -> "Classify";
  "defuddle" -> "Classify";
  "Text" -> "Classify";
  "Classify" -> "Tag & Frontmatter";
  "Tag & Frontmatter" -> "Write .md to vault";
  "Write .md to vault" -> "Update MOC";
}

Step 1: Extract Content

Web Page (default)

defuddle parse <url> --md -o /tmp/obsidian-import.md

YouTube / Bilibili

# YouTube
yt-dlp --write-auto-sub --sub-lang zh,en --skip-download --convert-subs srt <url> -o /tmp/obsidian-import

# Bilibili
yt-dlp --write-sub --sub-lang zh-Hans --skip-download --convert-subs srt <url> -o /tmp/obsidian-import

Raw Text

Use input directly, no extraction needed.

Step 2: Auto-Classify

Step 3: Auto-Tag

Scan title + first 500 chars for these topics and add as frontmatter tags:

AI, 投资, 教育, 数学, 编程, 芯片, 自动驾驶, 电动车, 全球化, 健康, 职业, 创业, 中国, 美国, 物理, 化学, 生物, 哲学, 历史, 经济

Step 4: Write Note

File: <vault>/<folder>/<clean-title>.md

---
source: <url or "manual">
kb: <folder>
date: YYYY-MM-DD
tags:
  - <auto-tag-1>
  - <auto-tag-2>
url: <original-url>
---

# <Title>

<extracted content>

Filename rules:

• Remove / \ : * ? " < > |
• Max 90 chars
• Deduplicate with _1, _2 suffix

Step 5: Update MOC

Append to <folder>-MOC.md:

- [[<filename-without-ext>|<title>]] (YYYY-MM-DD)

Quick Reference