blog-notebooklm
Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for source-grounded research context. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".
npx skills add AgriciDaniel/claude-blog --skill blog-notebooklm --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Blog NotebookLM: Source-Grounded Research from Your Documents Query Google NotebookLM notebooks directly from Claude Code for citation-backed answers from Gemini. Each question opens a headless browser session, retrieves the answer from your uploaded documents, and closes. Responses are source-grounded model answers, not proof of truth: uploaded documents may be primary or secondary, and the answer can still omit context. Answers provide usable provenance only when the returned citation identifies a verifiable underlying source. Record a stable source URL and a publication, study-period, or retrieval date when that detail affects verification or interpretation. Use the underlying source title as the inline citation. Do not cite the private NotebookLM URL as the bibliography entry for public content. ## Quick Reference | Command | What it does | |---------|-------------| | `/blog notebooklm ask <question>` | Query a notebook for source-grounded answers | | `/blog notebooklm discover <url>` | Smart-discover notebook content before cataloging | | `/blog notebooklm library list` | List all notebooks in library | | `/blog notebooklm library add <url>` | Add a notebook to library | | `
- Quick Reference
- Prerequisites
- Use the run.py Wrapper
- Auth Check (Gate Pattern)
- Setup Workflow
- Query Workflow
- Step 1: Check Auth
- Step 2: Resolve Notebook
- Step 3: Ask the Question
- Step 4: Analyze and Follow Up
- Smart Discovery Workflow
- Library Management
- Internal API (for blog-write / blog-researcher)
- Data Storage
python3 scripts/run.py auth_manager.py status python3 scripts/run.py ask_question.py --question "..." Do not call files under scripts/ directly. The wrapper owns venv setup. Opens a visible browser for manual Google login (one-time) python3 scripts/run.py auth_manager.py setup python3 scripts/run.py auth_manager.py status # Check auth python3 scripts/run.py auth_manager.py reauth # Re-authenticate python3 scripts/run.py auth_manager.py clear # Clear all auth data Basic query (uses active notebook) python3 scripts/run.py ask_question.py --question "Your question here"
What does the blog-notebooklm skill do?
Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for source-grounded research context. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".
How do I install it?
Run `npx skills add AgriciDaniel/claude-blog --skill blog-notebooklm --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From AgriciDaniel/claude-blog, a repository with 1,566 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.