Agent skill · bighardperson
notebooklm-studio
Import sources (URLs, YouTube, files, text) into Google NotebookLM and generate artifacts: podcasts, videos, reports, quizzes, flashcards, mind maps, slide decks, infographics, data tables. Use when users want to study from web content, create learning materials from URLs or documents, generate quizzes from articles, or produce study aids.
What it needs
About 2k tokens when loaded.
What this skill does
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: zhHant): applied via notebooklm language set Artifact options: format, style, length, difficulty, etc. Custom instructions (optional): passed as description to generate commands Workflow Steps are sequential gates — do NOT skip or combine steps. 0. Auth precheck — Verify the session is valid: 1. Parse input & configure artifacts — 1a. Select artifacts 1b. Discuss options (ASK / OFFER / SILENT priority levels) 2. Derive slug — Generate a short kebab-case slug for the notebook name and output directory. 3. Create notebook — 4. Set language — notebooklm language set <confirmedlanguage> 5. Add sources — For each source: notebooklm source add "<urlorfilepath>" 6. Generate artifacts — Two-tier strategy: Tier 1 (Immediate): mind-map, report, quiz, flashcards, data-table, infographic — use --wait Tier 2 (Deferred): slide-deck, video, audio — use --json, capture taskid for polling 7. Download Tier 1 — Each artifact into ./output/<slug>/ 8. Report + Deliver Tier 1 — Present completed artifacts to user 9. Poll + Deliver Tier 2 — Wait for deferred artifacts, download and deliver as each completes Artifact Types Type Tier Typical Time ------ ------ ------------- mind-map 1 Instant report 1 1-2 min quiz 1 1-2 min flashcards 1 1-2 min data-table 1 1-2 min infographic 1 2-5 min slide-deck 2 5-15 min video 2 10-30 min audio (podcast) 2 10-30 min Requirements notebooklm CLI (notebooklm-py) ffmpeg (for audio compression) playwright (for browser automation) Error Handling Auth errors: Caught by step 0 precheck. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills bighardperson/NotebookLM Studio