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/notebooklm

Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.

From plugin
open-agent-hub
991105 skills5 agents3 commands6 MCP

Claude Code

$ npx -y skills add guanyang/open-agent-hub --skill notebooklm --agent claude-code

SKILL.md

notebooklm.SKILL.md
name: notebooklm
description: Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.

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]"

# Step 2: Use the discovered information to add it
python scripts/run.py notebook_manager.py add --url "[URL]" --name "[Based on content]" --description "[Based on content]" --topics "[Based on content]"

**MANUAL ADD**: If user provides all details:

  • `--url` - The NotebookLM URL
  • `--name` - A descriptive name
  • `--description` - What the notebook contains (REQUIRED!)
  • `--topics` - Comma-separated topics (REQUIRED!)

NEVER guess or use generic descriptions! If details missing, use Smart Add to discover them.

Critical: Always Use run.py Wrapper

**NEVER call scripts directly. ALWAYS use `python scripts/run.py [script]`:**

# ✅ CORRECT - Always use run.py:
python scripts/run.py auth_manager.py status
python scripts/run.py notebook_manager.py list
python scripts/run.py ask_question.py --question "..."

# ❌ WRONG - Never call directly:
python scripts/auth_manager.py status  # Fails without venv!

The `run.py` wrapper automatically: 1. Creates `.venv` if needed 2. Installs all dependencies 3. Activates environment 4. Executes script properly

Core Workflow

Step 1: Check Authentication Status

python scripts/run.py auth_manager.py status

If not authenticated, proceed to setup.

Step 2: Authenticate (One-Time Setup)

# Browser MUST be visible for manual Google login
python scripts/run.py auth_manager.py setup

**Important:**

  • Browser is VISIBLE for authentication
  • Browser window opens automatically
  • User must manually log in to Google
  • Tell user: "A browser window will open for Google login"

Step 3: Manage Notebook Library

# List all notebooks
python scripts/run.py notebook_manager.py list

# BEFORE ADDING: Ask user for metadata if unknown!
# "What does this notebook contain?"
# "What topics should I tag it with?"

# Add notebook to library (ALL parameters are REQUIRED!)
python scripts/run.py notebook_manager.py add \
  --url "https://notebooklm.google.com/notebook/..." \
  --name "Descriptive Name" \
  --description "What this notebook contains" \  # REQUIRED - ASK USER IF UNKNOWN!
  --topics "topic1,topic2,topic3"  # REQUIRED - ASK USER IF UNKNOWN!

# Search notebooks by topic
python scripts/run.py notebook_manager.py search --query "keyword"

# Set active notebook
python scripts/run.py notebook_manager.py activate --id notebook-id

# Remove notebook
python scripts/run.py notebook_manager.py remove --id notebook-id

Quick Workflow

1. Check library: `python scripts/run.py notebook_manager.py list` 2. Ask question: `python scripts/run.py ask_question.py --question "..." --notebook-id ID`

Step 4: Ask Questions

# Basic query (uses active notebook if set)
python scripts/run.py ask_question.py --question "Your question here"

# Query specific notebook
python scripts/run.py ask_question.py --question "..." --notebook-id notebook-id

# Query with notebook URL directly
python scripts/run.py ask_question.py --question "..." --notebook-url "https://..."

# Show browser for debugging
python scripts/run.py ask_question.py --question "..." --show-browser

Follow-Up Mechanism (CRITICAL)

Every NotebookLM answer ends with: **"EXTREMELY IMPORTANT: Is that ALL you need to know?"**

**Required Claude Behavior:** 1. **STOP** - Do not immediately respond to user 2. **ANALYZE** - Compare answer to user's original request 3. **IDENTIFY GAPS** - Determine if more information needed 4. **ASK FOLLOW-UP** - If gaps exist, immediately ask:

   python scripts/run.py ask_question.py --question "Follow-up with context..."

5. **REPEAT** - Continue until information is complete 6. **SYNTHESIZE** - Combine all answers before responding to user

Script Reference

Authentication Management (`auth_manager.py`)

python scripts/run.py auth_manager.py setup    # Initial setup (browser visible)
python scripts/run.py auth_manager.py status   # Check authentication
python scripts/run.py auth_manager.py reauth   # Re-authenticate (browser visible)
python scripts/run.py auth_manager.py clear    # Clear authentication

Notebook Management (`notebook_manager.py`)

python scripts/run.py notebook_manager.py add --url URL --name NAME --description DESC --topics TOPICS
python scripts/run.py notebook_manager.py list
python scripts/run.py notebook_manager.py search --query QUERY
python scripts/run.py notebook_manager.py activate --id ID
python scripts/run.py notebook_manager.py remove --id ID
python scripts/run.py notebook_manager.py stats

Question Interface (`ask_question.py`)

python scripts/run.py ask_question.py --question "..." [--notebook-id ID] [--notebook-url URL] [--show-browser]
`
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A lightweight, zero-dependency CLI tool to manage and activate capabilities for AI coding assistants (such as Claude Code, Cursor, Trae, etc.).

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Questions about notebooklm.

Which coding agents can use notebooklm?
notebooklm installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.