Tencent SkillHub · Developer Tools

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.

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: AUTHENTICATION.md, CHANGELOG.md, README.md, SKILL.md, references/api_reference.md, references/troubleshooting.md

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

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New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

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I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 0.1.0

Provenance

Publisher: guccidgi
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 22 sections Open source page

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: Creates .venv if needed Installs all dependencies Activates environment Executes script properly

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

Check library: python scripts/run.py notebook_manager.py list 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: STOP - Do not immediately respond to user ANALYZE - Compare answer to user's original request IDENTIFY GAPS - Determine if more information needed ASK FOLLOW-UP - If gaps exist, immediately ask: python scripts/run.py ask_question.py --question "Follow-up with context..." REPEAT - Continue until information is complete SYNTHESIZE - Combine all answers before responding to user

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]

Data Cleanup (cleanup_manager.py)

python scripts/run.py cleanup_manager.py # Preview cleanup python scripts/run.py cleanup_manager.py --confirm # Execute cleanup python scripts/run.py cleanup_manager.py --preserve-library # Keep notebooks

Environment Management

The virtual environment is automatically managed: First run creates .venv automatically Dependencies install automatically Chromium browser installs automatically Everything isolated in skill directory Manual setup (only if automatic fails): python -m venv .venv source .venv/bin/activate # Linux/Mac pip install -r requirements.txt python -m patchright install chromium

Data Storage

All data stored in ~/.claude/skills/notebooklm/data/: library.json - Notebook metadata auth_info.json - Authentication status browser_state/ - Browser cookies and session Security: Protected by .gitignore, never commit to git.

Configuration

Optional .env file in skill directory: HEADLESS=false # Browser visibility SHOW_BROWSER=false # Default browser display STEALTH_ENABLED=true # Human-like behavior TYPING_WPM_MIN=160 # Typing speed TYPING_WPM_MAX=240 DEFAULT_NOTEBOOK_ID= # Default notebook

Decision Flow

User mentions NotebookLM ↓ Check auth → python scripts/run.py auth_manager.py status ↓ If not authenticated → python scripts/run.py auth_manager.py setup ↓ Check/Add notebook → python scripts/run.py notebook_manager.py list/add (with --description) ↓ Activate notebook → python scripts/run.py notebook_manager.py activate --id ID ↓ Ask question → python scripts/run.py ask_question.py --question "..." ↓ See "Is that ALL you need?" → Ask follow-ups until complete ↓ Synthesize and respond to user

Troubleshooting

ProblemSolutionModuleNotFoundErrorUse run.py wrapperAuthentication failsBrowser must be visible for setup! --show-browserRate limit (50/day)Wait or switch Google accountBrowser crashespython scripts/run.py cleanup_manager.py --preserve-libraryNotebook not foundCheck with notebook_manager.py list

Best Practices

Always use run.py - Handles environment automatically Check auth first - Before any operations Follow-up questions - Don't stop at first answer Browser visible for auth - Required for manual login Include context - Each question is independent Synthesize answers - Combine multiple responses

Limitations

No session persistence (each question = new browser) Rate limits on free Google accounts (50 queries/day) Manual upload required (user must add docs to NotebookLM) Browser overhead (few seconds per question)

Resources (Skill Structure)

Important directories and files: scripts/ - All automation scripts (ask_question.py, notebook_manager.py, etc.) data/ - Local storage for authentication and notebook library references/ - Extended documentation: api_reference.md - Detailed API documentation for all scripts troubleshooting.md - Common issues and solutions usage_patterns.md - Best practices and workflow examples .venv/ - Isolated Python environment (auto-created on first run) .gitignore - Protects sensitive data from being committed

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

6 Docs

SKILL.md Primary doc
AUTHENTICATION.md Docs
CHANGELOG.md Docs
README.md Docs
references/api_reference.md Docs
references/troubleshooting.md Docs