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notebooklm-import

Import NotebookLM notebooks into your Obsidian vault as linked knowledge graphs. Sources become wikilink-able files, Q&A answers get citations resolved to [[wikilinks]] with passage-level deep links. Use when user says "notebooklm import", "import notebook", "notebooklm sources", or wants to import NotebookLM data into vault files.

中文简介正在准备中。当前显示原文说明。

ArtemXTech/personal-os-skills星标 543(GitHub 543 + cccskills 0)
集成工具YouTubeObsidian

实测评分 未实测

查看安装方法

包含的文件(8)

  • SKILL.md3.5 KB
  • scripts/extract_passages.py4.8 KB
  • scripts/import_sources.py4.3 KB
  • scripts/resolve_citations.py10.1 KB
  • templates/dashboard.md384 B
  • templates/notebook-source.md209 B
  • workflows/ask.md3.8 KB
  • workflows/import.md2.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

NotebookLM - Vault Knowledge Graph

Turn NotebookLM notebooks into persistent, linked vault knowledge. Sources become files you can [[wikilink]], Q&A answers get [N] citations resolved to those wikilinks, dashboards tie it all together.

Prerequisites

1. Install notebooklm-py

pip install "notebooklm-py[browser]"
playwright install chromium

2. Authenticate

notebooklm login

Opens a browser window - log in with your Google account. Cookies are saved to ~/.notebooklm/storage_state.json.

Re-run notebooklm login when cookies expire (you'll see auth errors).

3. Obsidian Plugins

  • Dataview (required) - citation tables and dashboard queries use Dataview/DataviewJS

4. Vault Setup

Copy the templates from templates/ into your vault:

  • templates/notebook-source.md -> Templates/Types/notebook-source.md
  • templates/dashboard.md -> use as reference when creating dashboards

Quick Start

# Check current notebook
notebooklm status

# Switch notebook
notebooklm use <notebook-id>

# List notebooks
notebooklm list

Workflow Routing

User saysWorkflow
"import notebook", "notebooklm import", "import sources"workflows/import.md
"notebooklm ask", "ask notebook", "Q&A"workflows/ask.md

Architecture

Your Vault
├── Notes/NotebookLM/{notebook-slug}/
│   ├── Sources/          # One .md per source (YouTube, PDF, web, etc.)
│   │   ├── Video Title.md
│   │   └── Article Title.md
│   └── QA/               # Q&A notes with resolved citations
│       └── 2026-02-23 Emerging Themes.md
└── Notes/Dashboards/
    └── My Research.md     # Dashboard with Dataview queries
  • Source files have type notebook-source with frontmatter: source_id, notebook_id, url, source_type, topics as [[wikilinks]]
  • Q&A notes have type reference with [N] citations resolved to [[Source Title#Passage N]] wikilinks
  • Dashboards use Dataview queries to list sources and Q&A notes

Data Model

notebook-source frontmatter:

type: notebook-source
source_id: "uuid"        # NotebookLM source ID
notebook_id: "uuid"      # NotebookLM notebook ID
url: ""                  # Original URL
source_type: youtube     # youtube, pdf, web, text, gdocs, gslides
status: active
date: YYYY-MM-DD
topics:
  - "[[Topic Name]]"     # AI-extracted topics as wikilinks
related:
  - "[[Notes/Dashboards/Dashboard Name]]"

Q&A reference frontmatter:

type: reference
status: current
date: YYYY-MM-DD
source: "notebooklm:{notebook-slug}"
related:
  - "[[Notes/Dashboards/Dashboard Name]]"

Scripts

ScriptPurpose
scripts/import_sources.pyImport sources as vault files with AI-generated guides and topics
scripts/extract_passages.pyExtract cited passages from Q&A into source files
scripts/resolve_citations.pyReplace [N] markers with [[wikilinks]] in Q&A answers

All scripts use Path.cwd() as vault root - run them from your vault directory.

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