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NotebookLM Automation

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Streamline your interactions with Google's NotebookLM.

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Free · Opens the source repo

What NotebookLM Automation does

NotebookLM Automation is a specialized skill designed for browser automation within Google’s NotebookLM environment. This skill allows users to perform various actions such as reading from existing notebooks, adding new sources, generating outputs like audio and video overviews, and creating new notebooks. It is particularly useful for those who regularly interact with NotebookLM and want to automate repetitive tasks, enhancing productivity and efficiency in managing their notes and resources.

The skill operates by first ensuring that a browser automation environment is available. If the required tools are not loaded, it will halt with a clear message, guiding the user on how to enable the necessary context. Once the environment is confirmed, the skill navigates to the NotebookLM interface, allowing users to interact with their notebooks through a series of guided prompts. This structured approach reduces the potential for errors and ensures that actions are executed smoothly.

Users can choose from several actions, including querying existing notebooks, adding sources like URLs or files, and generating various outputs such as reports and infographics. Each action is designed to follow a specific workflow, ensuring that the skill captures the necessary information to execute the request accurately. The ability to customize prompts for generated outputs further enhances the quality of the results, making this skill a valuable tool for anyone looking to leverage NotebookLM more effectively.

This automation skill is ideal for developers, researchers, and anyone who frequently uses NotebookLM for note-taking, study guides, or project management. By automating these tasks, users can focus more on content creation and analysis rather than manual interactions with the platform.

When to use it

Use this skill when you need to automate tasks in NotebookLM, such as querying notebooks or generating reports.

When not to use it

This skill is not suitable for users who do not have a browser automation environment set up or those who require functionality outside of NotebookLM.

What you can build with it

Automating Note Queries

Quickly ask questions about existing notebooks without manual navigation, saving time during research.

Adding Resources Efficiently

Easily add URLs, text, or files to your notebooks through automated prompts, streamlining the resource management process.

Generating Reports and Overviews

Create detailed reports or multimedia overviews from your notebooks with customized prompts, enhancing presentation quality.

How to install NotebookLM Automation

View source

1. Install with the skills CLI

npx skills add alirezarezvani/claude-skills/notebooklm --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by alirezarezvani

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.

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)
# 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 Build pattern: Path B (direct conversion). Browser-automation shape — distinct from research-pack convention.

Frequently asked questions about NotebookLM Automation

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