Cs Notebooklm

/cs:notebooklm — NotebookLM browser automation. Action-routing intake (Q1: read / add source / Studio output / create new) + per-action Q2-Q4 branching. Fire-and-notify for slow Studio ops. Mandatory custom prompts (defaults are mediocre). Requires browser automation environment — fails clean on web.

Published by @Alireza Rezvani·0 agent reads / 30d·0 saves·

/cs:notebooklm — NotebookLM Browser Automation

Command: /cs:notebooklm

The cs-notebooklm persona controls Google NotebookLM via browser automation across 4 core actions.

Critical Prerequisite

Requires browser automation environment. Works in:

  • Claude Code CLI with computer-use
  • Claude Chrome Extension
  • Playwright / Puppeteer with screenshot + click tools

Does NOT work in:

  • Claude.ai web (no browser automation) — skill exits cleanly at Step 0

When to Run

  • Want to ask your existing NotebookLM notebook a question (Action 1)
  • Want to add a source (URL / text / file / Google Doc / YouTube) to a notebook (Action 2)
  • Want to generate a Studio output (Audio Overview / Infographic / Slides / Study Guide / etc.) (Action 3)
  • Want to create a new notebook from scratch (Action 4)

Action-Routing Intake (2-4 Forcing Questions)

QAsksNotes
Q1Action: read / add source / Studio output / create newForcing — refuses to start without commitment
Q2Notebook name or URL (actions 1-3) OR title for new notebook (action 4)Drives navigation
Q3Action-specific parameter (question text / source type / Studio output type / initial sources)Branches per Q1
Q4Studio custom prompt detailAsked only if Q1=3 (Studio); mandatory

Most invocations stop at Q3. Q4 only fires for Studio generation.

What You Get

Per action:

ActionResult
Read/ExtractClean response from notebook chat (not raw dump)
Add SourcesConfirmation of ingestion (with screenshot)
Studio OutputConfirmation that generation started + "NotebookLM will notify you when ready" — fire-and-notify
Create NewNew notebook URL + confirmation of initial sources added

Studio Output Types

All 9 types supported:

  • Audio Overview (5-10 min generation — fire-and-notify)
  • Study Guide
  • Briefing Doc
  • Timeline
  • FAQ
  • Table of Contents
  • Infographic
  • Slides (slide deck)
  • Mind Map

Mandatory Custom Prompts

Default Studio prompts produce mediocre output. The skill ALWAYS opens the customization menu and writes a detailed custom prompt before submitting.

Examples per output type:

OutputExample custom prompt
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"
Slides"12 slides max, 1-2 sentences per slide, presenter notes with examples per slide"

Discipline

  • Step 0 environment check — verify browser automation; fail fast if not
  • Screenshot-first — every UI action preceded by screenshot
  • find()-before-click — semantic finders over pixel coordinates
  • Never auto-handle login — detect login wall, stop, tell user to log in manually
  • Studio custom prompts always — open customization menu, write detailed prompt
  • Fire-and-notify for slow ops — Studio generation doesn't block this session
  • Tool-agnostic language — "browser automation tool", not "Claude Chrome Extension"

Trigger Phrases (auto-invoke without /cs:)

  • "open NotebookLM"
  • "check my [notebook name] notebook"
  • "pull info from NotebookLM"
  • "ask my notebook about X"
  • "add [source] to NotebookLM"
  • "create an infographic in NotebookLM"
  • "use NotebookLM Studio"
  • "generate a slide deck from my notebook"
  • "what does my notebook say about X"
  • Any variation involving NotebookLM

Workflow

# Step 0: environment check (silent if available; halt if not)

# Phase 0 intake (Q1 + Q2 minimum; Q3-Q4 branch per action)
python ../skills/notebooklm/scripts/action_router.py \
  --action read_extract --notebook "Q3 prep" --question "what are the latest trends?"

# Studio output flow includes custom prompt generation:
python ../skills/notebooklm/scripts/custom_prompt_template_generator.py \
  --output-type infographic --audience executive --length compact

# Async classification (for "should I wait or fire-and-notify?")
python ../skills/notebooklm/scripts/async_action_classifier.py --action audio_overview
# Returns: FIRE_AND_NOTIFY (5-10 min generation)

# Execute action via browser automation (screenshot → find → click → verify)
# Return clean summary

Stop Conditions

  • Browser automation unavailable → halt at Step 0 with clear message
  • Q1 action commitment refused → halt, re-ask
  • Login wall detected → halt, ask user to log in manually
  • Page layout changed unexpectedly → screenshot, ask user for guidance
  • 3 consecutive UI find() failures → halt, alert user

Anti-Patterns Rejected

  • Tool-specific 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)

Related

  • Agent: cs-notebooklm
  • Skill: notebooklm
  • Source spec: megaprompts/03-notebooklm-megaprompt.md
  • Research-domain siblings (different shape): /cs:pulse, /cs:litreview, /cs:grants, /cs:dossier, /cs:patent, /cs:syllabus

Version: 1.0.0 Source: Path-B direct conversion of megaprompts/03-notebooklm-megaprompt.md

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