A workflow for asking questions about documents stored in Google NotebookLM, a service that answers from a user’s uploaded sources. It uses browser automation and returns answers grounded in those documents.

It is for querying notebooks, checking documentation, adding notebooks to a managed library, and getting answers based on uploaded sources.

It helps reduce unsupported answers by keeping research tied to the documents in a notebook.

notebooklm — Skill for Claude Code and Codex by CommandCodeAI

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add CommandCodeAI/agent-skills --skill notebooklm-skill

Clone the repo

git clone --depth 1 https://github.com/CommandCodeAI/agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/commandcodeai/agent-skills/notebooklm-skill/github.svg)](https://agentmods.dev/skills/commandcodeai/agent-skills/notebooklm-skill)

Your own site

<a href="https://agentmods.dev/skills/commandcodeai/agent-skills/notebooklm-skill"><img src="https://agentmods.dev/badge/skills/commandcodeai/agent-skills/notebooklm-skill/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/commandcodeai/agent-skills/notebooklm-skill"><img src="https://agentmods.dev/badge/skills/commandcodeai/agent-skills/notebooklm-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,112 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 100% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00049	$0.02112
Opus 5.5	$0.00020	$0.00845
Sonnet 5.5	$0.00010	$0.00422
Haiku 4.5	$0.00005	$0.00211

Measured 1mo ago against content hash 8fcfe1aa0452, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

notebooklm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 10 executable files (scripts/__init__.py, scripts/ask_question.py, scripts/auth_manager.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to notebooklm — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/notebooklm-skill/SKILL.md · 270 lines

How it starts

The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 270 lines

Files

What ships with it

14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 270 lines · 49 tokens per session scan A 8fcfe1aa0452

Subscribe to this mod's changes

notebooklm is a skill published in the GitHub repository CommandCodeAI/agent-skills (137 stars, last pushed 7mo ago), licensed MIT. It adds 49 tokens to every session and 2,112 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to notebooklm, differing in 0 lines, and is treated as a copy.

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