Agent skill
notebooklm
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 ask", "notebooklm sources", or wants to turn NotebookLM research into vault knowledge.
Install this agent skill to your Project
npx add-skill https://github.com/ArtemXTech/personal-os-skills/tree/main/skills/notebooklm
SKILL.md
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.mdtemplates/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 says | Workflow |
|---|---|
| "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-sourcewith frontmatter:source_id,notebook_id,url,source_type, topics as[[wikilinks]] - Q&A notes have type
referencewith[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
| Script | Purpose |
|---|---|
scripts/import_sources.py |
Import sources as vault files with AI-generated guides and topics |
scripts/extract_passages.py |
Extract cited passages from Q&A into source files |
scripts/resolve_citations.py |
Replace [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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