How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does notebooklm support?

notebooklm works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is notebooklm free to use?

Yes. notebooklm is free to install and use. It is available from the open explainx.ai skill registry published by pleaseprompto.

Where can I read ratings and reviews for notebooklm?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install notebooklm?

Run `npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm` in your terminal. You need to have run `npx skills init` once in your project first.

Productivity

notebooklm▌

pleaseprompto/notebooklm-skill · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm

0 commentsdiscussion

summary

Query your Google NotebookLM notebooks directly from Claude for source-grounded, citation-backed answers.

›Automates browser-based interaction with NotebookLM to retrieve answers exclusively from your uploaded documents, eliminating hallucinations through document-only responses
›Manages notebook library with metadata tagging, search, and activation; supports smart discovery of notebook content when adding new sources
›Handles persistent authentication via one-time Google login setup wi

skill.md

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

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

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

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]

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

Problem	Solution
ModuleNotFoundError	Use `run.py` wrapper
Authentication fails	Browser must be visible for setup! --show-browser
Rate limit (50/day)	Wait or switch Google account
Browser crashes	`python scripts/run.py cleanup_manager.py --preserve-library`
Notebook not found	Check 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

how to use notebooklm

How to use notebooklm on Cursor

AI-first code editor with Composer

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add notebooklm

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/pleaseprompto/notebooklm-skill --skill notebooklm

The skills CLI fetches notebooklm from GitHub repository pleaseprompto/notebooklm-skill and configures it for Cursor.

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ── always included ────

│ • Amp

│ • Antigravity

│ • Cline

│ • Codex

│ ●Cursor(selected)

│ • Cursor

│ • Windsurf

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/notebooklm

Reload or restart Cursor to activate notebooklm. Access the skill through slash commands (e.g., /notebooklm) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub ›Skills CLI documentation ›Learn more about Cursor ›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

✓

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

✓

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

✓

Save 3-5 hours/week on communication overhead

Implementation Guide▌

Prerequisites

›Claude Desktop or compatible AI client
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

1.Install product management skill
2.Start with user story generation for known feature
3.Progress to competitive analysis: research 2-3 competitors
4.Use for roadmap prioritization: apply RICE/ICE scoring
5.Draft stakeholder communications and refine based on feedback
6.Build template library for recurring PM tasks
7.Share effective prompts with product team

Common Pitfalls

⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements

Best Practices▌

✓ Do

+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition

✗ Don't

−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture

💡 Pro Tips

★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs

When to Use This▌

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path▌

1Basic: user stories, feature specs, status updates
2Intermediate: competitive analysis, prioritization frameworks, PRDs
3Advanced: product strategy, go-to-market planning, OKR setting
4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)

No comments yet — start the thread.

general reviews

Ratings

4.6★★★★★71 reviews

★★★★★Anika Iyer· Dec 28, 2024
notebooklm fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
★★★★★Anika Robinson· Dec 24, 2024
notebooklm has been reliable in day-to-day use. Documentation quality is above average for community skills.
★★★★★Li Verma· Dec 24, 2024
notebooklm is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
★★★★★Kabir Iyer· Dec 12, 2024
Registry listing for notebooklm matched our evaluation — installs cleanly and behaves as described in the markdown.
★★★★★Kiara Johnson· Nov 19, 2024
We added notebooklm from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
★★★★★Yusuf Li· Nov 19, 2024
Registry listing for notebooklm matched our evaluation — installs cleanly and behaves as described in the markdown.
★★★★★Hassan Smith· Nov 15, 2024
notebooklm reduced setup friction for our internal harness; good balance of opinion and flexibility.
★★★★★Chinedu Singh· Nov 15, 2024
Keeps context tight: notebooklm is the kind of skill you can hand to a new teammate without a long onboarding doc.
★★★★★Li Tandon· Nov 11, 2024
We added notebooklm from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
★★★★★Yuki Taylor· Nov 3, 2024
notebooklm fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

showing 1-10 of 71

1 / 8

notebooklm▌

NotebookLM Research Assistant Skill

When to Use This Skill

⚠️ CRITICAL: Add Command - Smart Discovery

Critical: Always Use run.py Wrapper

Core Workflow

Step 1: Check Authentication Status

Step 2: Authenticate (One-Time Setup)

Step 3: Manage Notebook Library

Quick Workflow

Step 4: Ask Questions

Follow-Up Mechanism (CRITICAL)

Script Reference

Authentication Management (auth_manager.py)

Notebook Management (notebook_manager.py)

Question Interface (ask_question.py)

Data Cleanup (cleanup_manager.py)

Environment Management

Data Storage

Configuration

Decision Flow

Troubleshooting

Best Practices

Limitations

Resources (Skill Structure)

How to use notebooklm on Cursor

Prerequisites

Execute installation command

Select Cursor when prompted

Verify installation

Security & Verification Notice

Additional Resources

List & Monetize Your Skill

Use Cases▌

User Story & Requirements Generation

Competitive Analysis

Roadmap Prioritization

Stakeholder Communication

Implementation Guide▌

Prerequisites

Time Estimate

Installation Steps

Common Pitfalls

Best Practices▌

✓ Do

✗ Don't

💡 Pro Tips

When to Use This▌

✓ Use When

✗ Avoid When

Learning Path▌

Discussion

Ratings

Authentication Management (`auth_manager.py`)

Notebook Management (`notebook_manager.py`)

Question Interface (`ask_question.py`)

Data Cleanup (`cleanup_manager.py`)