Notebooklm
The NotebookLM Research Assistant skill enables Claude Code users to query their Google NotebookLM notebooks directly, retrieving source-grounded answers from uploaded documents with automatic citations while minimizing hallucinations. It solves the problem of accessing document-based information reliably by automating browser-based queries to NotebookLM and managing notebook libraries through Python scripts that handle authentication, notebook management, and question answering. The skill is designed for researchers, analysts, and knowledge workers who need to reference specific documentation without relying on general model knowledge.
- skills.sh installs
- 7.8K
- GitHub stars
- 7.8K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add pleaseprompto/notebooklm-skill --skill notebooklm --agent claude-codeInstalls into .claude/skills of the current project.
Files
NotebookLM Research Assistant Skill
Interact with Google NotebookLM to query documentation with Gemini's source-grounded answers. Each question opens a fresh browser session, retrieves the answer exclusively from your uploaded documents, and closes.
When to Use This Skill
Trigger when user:
- Mentions NotebookLM explicitly
- Shares NotebookLM URL (
https://notebooklm.google.com/notebook/...) - Asks to query their notebooks/documentation
- Wants to add documentation to NotebookLM library
- Uses phrases like "ask my NotebookLM", "check my docs", "query my notebook"
⚠️ CRITICAL: Add Command - Smart Discovery
When user wants to add a notebook without providing details:
SMART ADD (Recommended): Query the notebook first to discover its content:
# Step 1: Query the notebook about its content
python scripts/run.py ask_question.py --question "What is the content of this notebook? What topics are covered? Provide a complete overview briefly and concisely" --notebook-url "[URL]"
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- Repository
- github.com/pleaseprompto/notebooklm-skill
- Categories
- Backend & APIs, Automation & Workflows
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