Agent skill

Notebooklm

by alirezarezvani in alirezarezvani/claude-skills

Browser automation skill for controlling Google's NotebookLM.

MITAuto-check passedKnowledge Management

Install Notebooklm

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill notebooklm -a claude-code

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

GitHub CLI
$ gh skill install alirezarezvani/claude-skills 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/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/research/notebooklm/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
28k
Token cost
~4k tokens
SKILL.md length
1,946 words
Files
7 (incl. scripts, references)
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

Browser automation skill for controlling Google's NotebookLM.

  • Works in 2 steps: Browser Context Setup (Mandatory) → Grill-Me Intake (Action-Routing)
  • The user wants anything done in NotebookLM (e.g.
  • SKILL.md covers Step 0: Browser Context Setup…, Phase 0: Grill-Me Intake…, Notebook Discovery and Action 1: Read / Extract, plus 12 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Notebooklm is an agent skill from alirezarezvani/claude-skills. Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ…

Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/async_action_discipline.md`, `references/browser_automation_canon.md` and `references/studio_output_custom_prompts.md`).

It sits in Knowledge Management, covering Source-grounded notebooks, Study guides and flashcards and Browser automation. It works with NotebookLM and YouTube. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • The user wants anything done in NotebookLM (e.g.
  • Open NotebookLM
  • Check my [name] notebook
  • Ask my notebook about X

Example prompts

  • “open NotebookLM”
  • “check my [name] notebook”
  • “ask my notebook about X”
  • “/notebooklm”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Browser Context Setup (Mandatory)
  2. Grill-Me Intake (Action-Routing)

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. 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 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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):

    • notebooklm.google.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 4k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 187 tokens; SKILL.md has 1,946 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~187
When it runs · the whole SKILL.md, loaded when a task matches
~4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~11k

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 alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,946 words, ~4,032 tokens.

Download SKILL.mdSave it as .claude/skills/notebooklm/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
notebooklm
description
Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.
license
MIT
metadata.source_spec
megaprompts/03-notebooklm-megaprompt.md
metadata.build_pattern
Path B (direct conversion)
metadata.shape
browser-automation (distinct from research-pack convention)
metadata.version
1.0.0

NotebookLM — Browser Automation

Requires: A browser automation environment (Claude Code CLI with computer-use, Claude Chrome Extension, or equivalent). Skill will gracefully fail in non-automation contexts with a clear "not supported" message.

Critical: This skill is the only browser-automation skill in the v2 collection. It does NOT follow the research-pack Agent Integrity Rules convention. Different constraints apply (UI dynamics, async generation, login walls).

Step 0: Browser Context Setup (Mandatory)

Before any other action, verify browser automation is available:

  1. Check whether browser-control tools are loaded in the harness (screenshot, click, find-element, navigate)
  2. If unavailable → halt with clear message: "This skill requires browser automation. Currently in {context}. Cannot proceed. Use Claude Code CLI with computer-use, Claude Chrome Extension, or equivalent."
  3. If available → take initial screenshot, navigate to https://notebooklm.google.com
  4. Detect login wall via screenshot. If login screen detected: halt with "Please log in to NotebookLM in the browser, then re-invoke this skill." Never attempt to handle login automatically.

Phase 0: Grill-Me Intake (Action-Routing)

Up to 4 forcing questions, one at a time, dependency-ordered. Most invocations stop at Q3.

Q1 (root) — Action

What do you want me to do? Pick one:

  1. Read / extract — ask a question of an existing notebook
  2. Add a source — push content (URL, text, file, Google Doc, or synthesized content) into a notebook
  3. Generate a Studio output — Audio/Video Overview, Mind Map, Report (Briefing Doc, Study Guide, FAQ, Timeline), Flashcards, Quiz, Infographic, or Slides — the exact set comes from the live Studio panel
  4. Create a new notebook — initialize with title + initial sources

Why I'm asking: Each action takes a different path through the UI and requires different parameters. Naming the action upfront prevents wasted screenshots and lets me ask only the follow-up questions that apply.

Forcing choice. If the user says "open NotebookLM" without specifying an action, refuse to start and re-ask Q1.

Q2 (depends on Q1) — Notebook identity

Which notebook? (asked for actions 1, 2, 3 — not for "create new")

Why I'm asking: If you give me a name, I'll search the homepage; if you give me a URL, I'll navigate directly. Names that are ambiguous will get a disambiguation prompt with screenshots.

For action 4 (create new): replace with "What's the title for the new notebook?"

Q3 (depends on Q1) — Action-specific parameter

Action 1 (read/extract):

"What's the question to ask the notebook? Use natural phrasing — the notebook's chat handles it best."

Action 2 (add source):

"What source type? Pick one:

  1. URL / website / YouTube link
  2. Copied text (paste here or point at content)
  3. File upload (provide absolute path)
  4. Google Doc (link)
  5. Synthesized content (I'll pre-process and add as 'Copied text')

Why I'm asking: Each source type goes through a different sub-flow in the Add Source dialog. Picking upfront saves a step."

Action 3 (Studio output):

"Which Studio output? As of 2026-06 the Studio panel offers Audio Overview, Video Overview, Mind Map, Reports (Briefing Doc / Study Guide / FAQ / Timeline / custom), Flashcards, Quiz, Infographic, and Slides — I'll screenshot the live panel and confirm what your account actually shows before clicking. And: any custom-prompt direction? Default prompts produce mediocre output — I always open the customization menu and write a detailed prompt. Tell me the angle or audience.

Why I'm asking: The output type sets the UI button to find. The custom prompt is mandatory for quality."

Action 4 (create new):

"Initial sources? Provide URLs, file paths, or 'I'll add later'."

Q4 (depends on Q1 = action 3) — Studio custom prompt detail

Tell me the angle, audience, and length for the Studio output. Examples:

  • Audio Overview: "Two-host conversation for a non-technical executive, 8–10 min, focus on business implications not technical depth"
  • Infographic: "Decision-tree style, action-oriented, 6 panels max, monochrome navy"
  • Study Guide: "Undergrad-level, definitions + 3 practice questions per concept"

Why I'm asking: This becomes the custom prompt. Default Studio prompts produce mediocre output — specific direction produces sharp output.

Asked only for Studio output generation (Q1=3). Skip otherwise.

Stop condition: After Q4 (or earlier with dependency skips), commit and start the action sequence.

See references/studio_output_custom_prompts.md for the canon.

Notebook Discovery

For actions 1-3 (require existing notebook):

  1. Navigate to homepage → screenshot
  2. If user provided URL → navigate directly
  3. If user provided name:
    • Use semantic find() to locate notebook card by visible title text
    • If multiple matches → screenshot homepage, list options, ask user to specify
    • If no match → ask user to provide URL or confirm spelling

For action 4 (create new):

  1. Locate "New notebook" button on homepage
  2. Click → set title from Q2
  3. Add initial sources per Q3

Action 1: Read / Extract

  1. Open the notebook (notebook discovery above)
  2. Locate chat input (semantic find or screenshot coordinates)
  3. Type the question (use the user's natural phrasing from Q3)
  4. Submit (Enter or send button)
  5. Wait 3–5 seconds
  6. Screenshot the response area
  7. Extract and present in clean format (not raw chat dump)

Action 2: Add Sources

Sub-flows per source type:

TypeUI flow
URL / Website / YouTubeAdd Source → Link → paste URL
Copied TextAdd Source → Copied text → paste content
File UploadUse file-upload tool with absolute path + input ref (never click native file picker)
Google DocAdd Source → Google Docs → Drive picker
Synthesized contentPre-process content elsewhere, then add as Copied text

After every add: wait for ingestion spinner, screenshot to confirm success.

Synthesized content pattern (powerful): instead of asking NotebookLM to ingest a raw URL with potentially noisy content, pre-process the content (extract main article, strip nav/ads/comments), then add as "Copied text". Produces dramatically better summarization.

Action 3: Studio Outputs

Discover, don't assume. NotebookLM's Studio inventory changes between rollouts and account tiers. As of the last verification (2026-06) the panel offers: Audio Overview, Video Overview, Mind Map, Reports (Briefing Doc, Study Guide, FAQ, Timeline, custom report formats), Flashcards, Quiz, Infographic, Slides. Treat this list as a hint, not ground truth — the screenshot of the live Studio panel is the authority. NotebookLM's UI evolves quickly; verify against the live product and update this section when it drifts (Studio inventory last verified 2026-06).

Mandatory workflow:

  1. Locate Studio panel (right side; may need toggle) and screenshot it — the tiles you see are the real output types for this account
  2. Find the specific output button for the requested type (if it isn't visible, check "Discover more"/overflow before declaring it unavailable)
  3. Open customization menu (chevron/arrow next to button) — NOT the main button
  4. Write detailed custom prompt (from Q4)
  5. Confirm and submit
  6. Do NOT wait for completion — confirm generation started, notify user, return
Custom prompt examples (4 output types)

Audio Overview:

"Two-host conversation between a researcher and an experienced practitioner. Audience: non-technical executive making a budget decision. Length: 8-10 minutes. Focus on business implications, not technical depth. Include one concrete example per major point. Acknowledge counter-arguments briefly."

Infographic:

"Decision-tree style. Action-oriented (each panel ends with a decision or action). 6 panels max. Monochrome navy + amber highlight. Each panel has: title (4-6 words), 1-2 sentence body, decision/action line. No filler panels."

Study Guide:

"Undergraduate-level (define every technical term). Structure: 6 concepts × 4 elements each (definition / why it matters / one worked example / 3 practice questions). Practice questions Bloom-higher-order (apply/analyze), not recall."

Slides (slide deck):

"12 slides max. 1-2 sentences per slide body. Presenter notes per slide with: one concrete example + one likely audience objection + how to address it. No bullet points in slide bodies — prose only. End with one-slide call-to-action."

See references/studio_output_custom_prompts.md for more.

Show full SKILL.md (713 more words)Show less

Action 4: Create New Notebook

  1. Navigate to homepage
  2. Click "New notebook"
  3. Set title from Q2
  4. Add initial sources from Q3 (use Action 2 sub-flows per source type)
  5. Wait for auto-summary generation (this one IS synchronous — usually completes in <30 sec)
  6. Screenshot final state

Critical Async Behavior

Async output rule: For Studio generations (especially Audio Overview — 5-10 min), DO NOT wait for completion. The user's session will time out.

Workflow: Click Generate → confirm generation has started via screenshot → tell the user "Generation in progress — NotebookLM will notify you when ready" → end the task.

This is the fire-and-notify pattern. Different from add-source and auto-summary (which are fast enough to wait).

Use scripts/async_action_classifier.py to determine wait-or-notify per action:

ActionWait?
Add Source (URL/text/file)Yes — wait for ingestion spinner (~5-30s)
Read/Extract (chat)Yes — wait 3-5s for response
Studio: Audio OverviewNo — fire and notify (5-10 min)
Studio: Video OverviewNo — fire and notify (5-15 min)
Studio: Infographic / Slides / Mind MapNo — fire and notify (2-5 min)
Studio: Study Guide / Briefing Doc / FAQ / Flashcards / QuizYes — wait ~30-60s
Create New NotebookYes — wait for auto-summary (<30s)
bash
# Verdict + paste-ready notify message for any action
python3 scripts/async_action_classifier.py --action "video overview"
# -> Verdict: FIRE_AND_NOTIFY, estimated 5-15 minutes, with the exact
#    "NOT waiting in this session" message to relay to the user

See references/async_action_discipline.md for the canon.

Screenshot-First Discipline

NotebookLM is a dynamic SPA where UI varies by:

  • Account tier (free vs Plus vs Enterprise)
  • Feature rollout (some Studio types not yet available to all users)
  • Recent UI changes (Google iterates the product frequently)

Every UI action must be preceded by a screenshot. Reasons:

  1. Verify the UI matches expectations before acting
  2. Catch login walls early
  3. Detect unexpected layout changes
  4. Audit trail for debugging

Use screenshot() (or equivalent in your browser-automation tool) before every meaningful UI interaction.

See references/browser_automation_canon.md for the discipline.

find()-Before-Click

Use semantic element finders before pixel coordinates wherever possible:

  • ✅ find(text="Audio Overview") → returns element regardless of position
  • ❌ click(x=420, y=380) → breaks when UI rearranges

Semantic finders survive minor UI changes. Pixel coordinates do not.

Only fall back to coordinates when:

  • Semantic find() returns nothing
  • Element has no stable text/aria-label/data-attribute
  • Visual position is the only reliable signal

Saving Outputs to Workspace

For Read/Extract actions producing useful information:

  1. Extract chat response cleanly (strip UI chrome)
  2. Format readably (paragraphs, lists, code blocks as appropriate)
  3. If user requested → save to file (${WORKSPACE}/notebooklm/<notebook-slug>-<action>-<date>.md)
  4. Otherwise → return in chat as final summary

For Studio outputs:

  1. NotebookLM hosts the output (Audio Overview is in-app, Infographic downloadable, etc.)
  2. Report the location (URL or in-app navigation path) to user
  3. Don't try to download/save Studio outputs to local workspace — that's NotebookLM's job

Reporting Back Format

After completing any action:

  1. Take final screenshot if visually relevant
  2. Give clean summary (not raw chat dump):
    • Notebook used (name)
    • Action taken (specific)
    • Result (1-2 sentences)
    • For generated outputs: what was created + where it is + when ready
  3. For fire-and-notify actions: explicit "NotebookLM will notify you when ready"

Error Handling

FailureBehavior
Browser automation unavailableFail fast with "this skill requires browser automation" message (Step 0 halt)
Login wall detectedStop. Tell user to log in. Don't attempt auto-login.
Multiple notebooks match nameScreenshot homepage, list options, ask user to specify
Source ingestion spinner stuck > 60sNote timeout, ask user if they want to retry
Studio button not found in panelScroll down or look for "Discover more"; if still missing, note feature may not be enabled for this account
Chat response doesn't appear in 10sScreenshot, check for error state, retry once
Page layout changed unexpectedlyScreenshot, describe what's visible, ask user for guidance

Tooling

ScriptRole
scripts/action_router.pyQ1-Q4 answers → action plan + UI flow + required parameters
scripts/custom_prompt_template_generator.pyStudio output type + audience + length → starter custom prompt
scripts/async_action_classifier.pyAction name → wait-or-notify pattern (fire-and-notify for slow generations)

References

Anti-Patterns To Reject

  • Tool-specific tool names without abstraction (e.g., hardcoding "Claude Chrome Extension")
  • Synchronous waiting on Studio generations (especially Audio Overview)
  • Skipping screenshots between actions
  • Using pixel coordinates when semantic find() is available
  • Attempting to handle login flows automatically
  • Generating Studio outputs without opening customization menu
  • Using default Studio prompts (always write custom)

Version: 1.0.0 Source spec: megaprompts/03-notebooklm-megaprompt.md (maintainer-local draft spec — gitignored, not present in the public repository) Build pattern: Path B (direct conversion). Browser-automation shape — distinct from research-pack convention.

© alirezarezvani, 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 6 other files (scripts, references) in research/notebooklm/skills/notebooklm of alirezarezvani/claude-skills.

  • SKILL.md
  • references/async_action_discipline.md
  • references/browser_automation_canon.md
  • references/studio_output_custom_prompts.md
  • scripts/action_router.py
  • scripts/async_action_classifier.py
  • scripts/custom_prompt_template_generator.py

Open the folder on GitHubat commit 19392f7

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 skillalirezarezvani/claude-skills28k—~4kAutomated safety check: PassMIT
Nlm Skilliusztinpaul/ai-research-os-workshop1791 repos~6.9kAutomated safety check: PassMIT
Notebooklm CLIItamarZand88/CLI-Anything-WEB231—~997Automated safety check: PassMIT
NotebookLM CLI Guidejacob-bd/notebooklm-cli256—~3.4kAutomated safety check: WarnMIT
NotebooklmMathews-Tom/armory328—~4kAutomated safety check: PassMIT
NotebookLM Research Workflowclaude-world/notebooklm-skill467—~1.8kAutomated safety check: PassMIT

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Questions about Notebooklm

What does Notebooklm do?

Browser automation skill for controlling Google's NotebookLM. Notebooklm is an agent skill from alirezarezvani/claude-skills. Browser automation skill for controlling Google's NotebookLM.

When should I use Notebooklm?

Notebooklm fits situations like: the user wants anything done in NotebookLM (e.g; open NotebookLM; check my [name] notebook; ask my notebook about X.

How do I install Notebooklm in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill notebooklm -a claude-code`. Or copy the skill folder (research/notebooklm/skills/notebooklm in alirezarezvani/claude-skills) 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 alirezarezvani/claude-skills --skill notebooklm -a codex`. Or copy the skill folder (research/notebooklm/skills/notebooklm in alirezarezvani/claude-skills) 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 alirezarezvani/claude-skills --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 Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Notebooklm access the network?

SKILL.md names 1 domain. As links in the text: notebooklm.google.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 (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Notebooklm use?

About 4k tokens (SKILL.md is roughly 16k 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 7.3k 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 CLI (ItamarZand88/CLI-Anything-WEB, 231 stars), NotebookLM CLI Guide (jacob-bd/notebooklm-cli, 256 stars) and Notebooklm (Mathews-Tom/armory, 328 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Notebooklm?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,891 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.