NotebookLM Studio

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name: notebooklm-studio description: > Import sources (URLs, YouTube, files, text) into Google NotebookLM and generate user-selected artifacts: podcast, video, report, quiz, flashcards, mind map, slides, infographic, data table. Use when the user sends content and asks to generate learning materials, podcasts, videos, or study packages. version: 2.1.2 metadata: openclaw: requires: bins: [notebooklm, ffmpeg] emoji: "🎙️"

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NotebookLM Studio

Import sources into NotebookLM, generate user-selected artifacts via CLI, download results locally.

Inputs

Collect from user message (ask only for missing fields):

Sources: URLs, YouTube links, text notes, or file attachments (PDF, Word, audio, image, Google Drive link)

Artifacts: User selects from 9 types (no default — always ask):

- audio (podcast), video, report, quiz, flashcards, mind-map, slide-deck, infographic, data-table

Language (optional, default: zh_Hant): applied via notebooklm language set

- ⚠️ This is a GLOBAL setting — affects all notebooks in the account

Artifact options (discussed in step 1b): format, style, length, difficulty, etc.

See references/artifact-options.md for all options per artifact type.

Custom instructions (optional): passed as description to generate commands

Telegram target (optional, OpenClaw only): chat_id for delivery

See references/source-types.md for source type detection rules. See references/artifacts.md for all 9 artifact types and CLI options.

Workflow

Steps are sequential gates — do NOT skip or combine steps. Each numbered step must complete before the next begins. In particular:

Step 0 (auth precheck) must run and pass before any other CLI command.

Step 1b (options discussion) must get user confirmation before generation. Do not assume defaults unless the user explicitly says "use defaults."

0. Auth precheck — Verify the session is valid before doing any work:

   notebooklm auth check --test --json
   

- "status": "ok" → proceed to step 1. - "status": "error" → stop immediately. Tell the user: > NotebookLM 登入已過期，請先重新登入（notebooklm login），完成後告訴我，我再繼續。 - Command itself fails (network error, CLI not found, etc.) → also stop and report the error. - --test is required — without it, only local checks run, which can pass even with an expired session. - When the user confirms re-login, re-run this check before continuing.

1. Parse input & configure artifacts —

1a. Select artifacts — Detect source types from user message (URLs, files, text). Confirm which artifacts to generate.

1b. Discuss options — Before generating, confirm key options for each selected artifact. Refer to references/artifact-options.md for priority levels: - ASK options: must ask the user - OFFER options: state the default, let user decide whether to change - SILENT options: use defaults without asking - Options already specified by the user → skip - Present all questions in a single message (batch, not one-by-one)

If user says "use defaults" → skip all questions, proceed with default values immediately.

Example agent message (audio + video + report + quiz + flashcards + slides + infographic selected): > Before generating, a few options to confirm: > - Podcast: deep-dive / brief / critique / debate? > - Video: explainer / brief / cinematic? (cinematic uses Veo 3, takes 30-40 min) > - Report: briefing-doc / study-guide / blog-post / custom? > - Slides: detailed / presenter? > - Quiz & Flashcards: difficulty medium, quantity standard — adjust? > - Infographic: style auto, or prefer a specific style (sketch-note, professional, bento-grid...)? > - Language: zh_Hant, OK? > > Or just say "use defaults" to start immediately.

2. Derive slug — Based on the sources and user message, generate a short kebab-case slug (2-4 words) that captures the core topic. This slug is used for both the notebook name and the output directory. - Examples: react-server-components, feynman-technique, taiwan-semiconductor-q4 - Keep it concise, lowercase, ASCII-only (transliterate non-ASCII if needed) - If the user provides a topic or title, prefer that as the basis

3. Create notebook —

   notebooklm create " "
   # → {"notebook_id": "xyz789", ...}  ← capture notebook_id
   notebooklm use 
   mkdir -p ./output/
   

4. Set language —

   notebooklm language set 
   

Use the language confirmed in step 1b. ⚠️ GLOBAL setting — always set explicitly to avoid residual from previous runs.

5. Add sources — For each source:

   # URL, YouTube, or file path
   notebooklm source add ""
   # Google Drive
   notebooklm source add-drive  "