Agent skill

Notebooklm

by roomi-fields in roomi-fields/notebooklm-mcp

This skill should be used when the user wants to query their Google NotebookLM notebooks for citation-backed, source-grounded answers, or manage notebooks, sources, and Studio content (audio…

MITAuto-check passedKnowledge Management

Install Notebooklm

skills CLI
$ npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install roomi-fields/notebooklm-mcp notebooklm --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/roomi-fields/notebooklm-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/notebooklm .claude/skills/notebooklm && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
notebooklm
GitHub stars
188
Token cost
~1.1k tokens
SKILL.md length
438 words
Files
4 (incl. scripts, references)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when the user wants to query their Google NotebookLM notebooks for citation-backed, source-grounded answers, or manage notebooks, sources, and Studio content (audio…

  • Works in 2 steps: notebooklm MCP tools — if tools such as… → HTTP REST API — otherwise, use the…
  • Wants to query their Google NotebookLM notebooks for citation-backed
  • SKILL.md covers Overview, Choosing the transport, Prerequisite: one Google login and Core tasks, plus 3 more sections
  • Runs Shell scripts from its folder; calls npm

What it does

Notebooklm is an agent skill from roomi-fields/notebooklm-mcp. This skill should be used when the user wants to query their Google NotebookLM notebooks for citation-backed, source-grounded answers, or manage notebooks, sources, and Studio content (audio, report, video, infographic, presentation, data table, flashcards, quiz, mind map). It drives the @roomi-fields/notebooklm-mcp engine — via the notebooklm MCP tools when they are available in the session, otherwise via its HTTP REST API — and covers Google login, citation formats, the daily-quota-aware batch/ingestion…

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/research-workflows.md`, `references/rest-api.md` and `scripts/nblm.sh`).

It sits in Knowledge Management, covering Source-grounded notebooks and MCP servers. It works with NotebookLM, Model Context Protocol, Google Gemini and TypeScript. The repository describes itself as: Google NotebookLM over MCP + a local HTTP REST API. Citation-backed Q&A, audio/video/content generation, multi-account rotation. For Claude Code, Codex, Cursor, n8n, Zapier, Make. The licence is MIT.

When your agent uses it

  • Wants to query their Google NotebookLM notebooks for citation-backed
  • Source-grounded answers
  • Manage notebooks
  • Studio content (audio

Example prompts

  • “/notebooklm”

Requirements

  • A Bash shell

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. notebooklm MCP tools — if tools such as notebook_ask / source_add /
  2. HTTP REST API — otherwise, use the bundled scripts/nblm.sh, which talks

What it can do on your machine

Read from SKILL.md and the folder at commit a05fe70. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Notebooklm loads about 1.1k tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 138 tokens; SKILL.md has 438 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~138
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from roomi-fields/notebooklm-mcp at commit a05fe70, republished under its MIT licence (© roomi-fields). 438 words, ~1,113 tokens.

Download SKILL.mdSave it as .claude/skills/notebooklm/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
notebooklm
description
This skill should be used when the user wants to query their Google NotebookLM notebooks for citation-backed, source-grounded answers, or manage notebooks, sources, and Studio content (audio, report, video, infographic, presentation, data table, flashcards, quiz, mind map). It drives the @roomi-fields/notebooklm-mcp engine — via the notebooklm MCP tools when they are available in the session, otherwise via its HTTP REST API — and covers Google login, citation formats, the daily-quota-aware batch/ingestion pattern, and source discovery.

NotebookLM

Overview

NotebookLM answers questions only from the sources uploaded to a notebook, with inline citations to the exact passages used — no open-web knowledge, so answers are hallucination-resistant and fully traceable. This skill drives the @roomi-fields/notebooklm-mcp engine to query notebooks, manage sources, and generate Studio content, and encodes the patterns that make NotebookLM usable at research scale (citation formats, the ~50-queries/day quota, batch-to-cache).

Choosing the transport

Two ways reach the same engine — pick per what the session already has:

  1. notebooklm MCP tools — if tools such as notebook_ask / source_add / server_health (or mcp__notebooklm__*) are available in the session, call them directly. This is the preferred path and needs no server.
  2. HTTP REST API — otherwise, use the bundled scripts/nblm.sh, which talks to a running NotebookLM MCP server (default http://localhost:3000, override with NOTEBOOKLM_SERVER_URL). If no server is reachable, ask the user to start one (npm run start:http from a clone) or to install the MCP.

Both are backed by the same account and session, so the choice is purely about which is already wired up.

Prerequisite: one Google login

NotebookLM needs a signed-in Google session (saved once, reused across runs). Verify with nblm.sh health (or the server_health tool) — look for authenticated: true. If not authenticated, run the interactive login in a terminal (a visible Chrome window opens):

bash
notebooklm-mcp-setup-auth          # global install
# or:  scripts/nblm.sh auth

Run the login in a terminal rather than through an in-client tool: interactive Google login can take minutes and a stdio client's tool-call timeout may cut it off.

Show full SKILL.md (195 more words)Show less

Core tasks

Use scripts/nblm.sh for the REST path (or the equivalent MCP tool):

bash
scripts/nblm.sh health                       # reachability + auth status
scripts/nblm.sh notebooks                     # list notebooks (id + name)
scripts/nblm.sh ask "<question>" <notebook_id>   # citation-backed answer (JSON citations)
scripts/nblm.sh generate <notebook_id> report   # audio|report|video|infographic|presentation|data_table|flashcards|quiz|mind_map
  • Ask: the script requests source_format: json, so the answer carries source names + cited excerpts. For a human-facing answer, prefer expanded (see references/rest-api.md to vary the format).
  • Generate: flashcards/quiz route to the study-aid endpoint and mind_map to the mind-map endpoint automatically.

Working effectively (read before large runs)

For anything beyond a few questions, load references/research-workflows.md. Key points:

  • Quota: free accounts cap at ~50 chat queries/day. Rotate accounts (/re-auth) or, better, ingest once and retrieve offline.
  • Batch → cache: for literature reviews / SOTA surveys, run an exhaustive question set through /batch-to-vault (writes markdown + nblm-answer-v1 JSON sidecars with citations), then answer repeated questions from the cache (e.g. with RTFM) — unlimited, offline.
  • Fresh vs. follow-up: omit session_id for independent questions (fastest); pass a stable one to continue a conversation.

References

  • references/rest-api.md — endpoint + body reference for the HTTP path.
  • references/research-workflows.md — citation formats, quota strategy, the batch/ingestion pattern, source discovery.

Installing the engine

If neither the MCP tools nor a server are present, the engine is the npm package @roomi-fields/notebooklm-mcp (also a Claude Code plugin via the roomi-fields/claude-plugins marketplace). Point the user there, then run the one-time login above.

© roomi-fields, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/notebooklm of roomi-fields/notebooklm-mcp.

  • SKILL.md
  • references/research-workflows.md
  • references/rest-api.md
  • scripts/nblm.sh

Open the folder on GitHubat commit a05fe70

Compare with similar skills

Notebooklm next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Notebooklm compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Notebooklm this skillroomi-fields/notebooklm-mcp188—~1.1kAutomated safety check: PassMIT
Nlm Skilliusztinpaul/ai-research-os-workshop1791 repos~6.9kAutomated safety check: PassMIT
NotebookLM Automationteng-lin/notebooklm-py20k—~4.1kAutomated safety check: PassMIT
Docsmint Document ManagerHiAi-gg/docsmint118—~584Automated safety check: PassApache-2.0
SEO APIseranking/seo-skills160—~4.1kAutomated safety check: PassMIT
Notebooklm Grounded ResearchAnastasiyaW/codex-claude-code-config154—~2.4kAutomated safety check: WarnMIT

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Questions about Notebooklm

What does Notebooklm do?

This skill should be used when the user wants to query their Google NotebookLM notebooks for citation-backed, source-grounded answers, or manage notebooks, sources, and Studio content (audio…. Notebooklm is an agent skill from roomi-fields/notebooklm-mcp. This skill should be used when the user wants to query their Google NotebookLM notebooks for citation-backed, source-grounded answers, or manage notebooks, sources, and Studio content (audio, report, video, infographic, presentation, data table, flashcards, quiz, mind map).

When should I use Notebooklm?

Notebooklm fits situations like: wants to query their Google NotebookLM notebooks for citation-backed; source-grounded answers; manage notebooks; studio content (audio.

How do I install Notebooklm in Claude Code?

Run `npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a claude-code`. Or copy the skill folder (skills/notebooklm in roomi-fields/notebooklm-mcp) into .claude/skills/notebooklm in your project. Claude Code loads it when a task matches its description.

How do I install Notebooklm in Codex?

Run `npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a codex`. Or copy the skill folder (skills/notebooklm in roomi-fields/notebooklm-mcp) into .agents/skills/notebooklm in your project. Codex loads it when a task matches its description.

Can I use Notebooklm in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/notebooklm, .gemini/skills/notebooklm, .github/skills/notebooklm and .opencode/skills/notebooklm in your project.

What does Notebooklm need to run?

Going by SKILL.md and its folder, Notebooklm needs a shell for the scripts in its folder and the command-line tools its instructions call (npm). Our summary lists: A Bash shell.

Does Notebooklm access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Notebooklm safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Notebooklm use?

Notebooklm is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Notebooklm use?

About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Notebooklm?

Skills that share tags, products or a category with Notebooklm: Nlm Skill (iusztinpaul/ai-research-os-workshop, 179 stars), NotebookLM Automation (teng-lin/notebooklm-py, 20k stars), Docsmint Document Manager (HiAi-gg/docsmint, 118 stars) and SEO API (seranking/seo-skills, 160 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Notebooklm?

roomi-fields (a GitHub user) maintains it in roomi-fields/notebooklm-mcp, which has 188 GitHub stars. The repository was last updated on September 4, 2026.

Source: roomi-fields/notebooklm-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.