AgentSkillsCN

notebooklm

借助此技能，您可以直接从Claude Code中查询Google NotebookLM笔记本，获取源自Gemini、有据可依且附带引用的答案。支持浏览器自动化、库管理以及持久化身份验证。Dr

SKILL.md
--- frontmatter
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. Dr
category: Document Processing
source: antigravity
tags: [python, api, claude, ai, automation, workflow, document, security, rag]
url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/notebooklm

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:

bash
# 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]:

bash
# ✅ 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

bash
python scripts/run.py auth_manager.py status

If not authenticated, proceed to setup.

Step 2: Authenticate (One-Time Setup)

bash
# 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

bash
# 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

bash
# 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:
    bash
    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)

bash
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