Programmatic access to Google NotebookLM with full artifact generation, source management, and download capabilities.
Works with
Create notebooks, add sources (URLs, PDFs, YouTube, audio, video, images), and chat with content via CLI or Python API
Generate all artifact types: podcasts, videos, slide decks, infographics, reports, quizzes, flashcards, mind maps, and data tables in multiple formats
Supports parallel agent workflows with explicit notebook IDs, subagent patterns for long-running ope
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionnotebooklmExecute the skills CLI command in your project's root directory to begin installation:
Fetches notebooklm from teng-lin/notebooklm-py and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate notebooklm. Access via /notebooklm in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
0
total installs
0
this week
9.3K
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
9.3K
stars
Complete programmatic access to Google NotebookLM—including capabilities not exposed in the web UI. Create notebooks, add sources (URLs, YouTube, PDFs, audio, video, images), chat with content, generate all artifact types, and download results in multiple formats.
From PyPI (Recommended):
pip install notebooklm-py
From GitHub (use latest release tag, NOT main branch):
# Get the latest release tag (using curl)
LATEST_TAG=$(curl -s https://api.github.com/repos/teng-lin/notebooklm-py/releases/latest | grep '"tag_name"' | cut -d'"' -f4)
pip install "git+https://github.com/teng-lin/notebooklm-py@${LATEST_TAG}"
⚠️ DO NOT install from main branch (pip install git+https://github.com/teng-lin/notebooklm-py). The main branch may contain unreleased/unstable changes. Always use PyPI or a specific release tag, unless you are testing unreleased features.
Skill install methods:
notebooklm skill install installs this skill into the supported local agent directories managed by the CLI.npx skills add teng-lin/notebooklm-py installs this skill from the GitHub repository into compatible agent skill directories.CLI-managed install:
notebooklm skill install
IMPORTANT: Before using any command, you MUST authenticate:
notebooklm login # Opens browser for Google OAuth
notebooklm list # Verify authentication works
If commands fail with authentication errors, re-run notebooklm login.
For automated environments, multiple accounts, or parallel agent workflows:
| Variable | Purpose |
|---|---|
NOTEBOOKLM_HOME |
Custom config directory (default: ~/.notebooklm) |
NOTEBOOKLM_PROFILE |
Active profile name (default: default) |
NOTEBOOKLM_AUTH_JSON |
Inline auth JSON - no file writes needed |
CI/CD setup: Set NOTEBOOKLM_AUTH_JSON from a secret containing your storage_state.json contents.
Multiple accounts: Use named profiles (notebooklm profile create work, then notebooklm -p work login). Alternatively, use different NOTEBOOKLM_HOME directories per account.
Parallel agents: The CLI stores notebook context in a shared file (~/.notebooklm/context.json). Multiple concurrent agents using notebooklm use can overwrite each other's context.
Solutions for parallel workflows:
-n <notebook_id> (for wait/download commands) or --notebook <notebook_id> (for others) instead of relying on useexport NOTEBOOKLM_PROFILE=agent-$ID (each profile gets its own context file)NOTEBOOKLM_HOME per agent: export NOTEBOOKLM_HOME=/tmp/agent-$IDBefore starting workflows, verify the CLI is ready:
notebooklm status → Should show "Authenticated as: email@..."notebooklm list --json → Should return valid JSON (even if empty notebooks list)notebooklm loginExplicit: User says "/notebooklm", "use notebooklm", or mentions the tool by name
Intent detection: Recognize requests like:
Run automatically (no confirmation):
notebooklm status - check contextnotebooklm auth check - diagnose auth issuesnotebooklm list - list notebooksnotebooklm source list - list sourcesnotebooklm artifact list - list artifactsnotebooklm language list - list supported languagesnotebooklm language get - get current languagenotebooklm language set - set language (global setting)notebooklm artifact wait - wait for artifact completion (in subagent context)notebooklm source wait - wait for source processing (in subagent context)notebooklm research status - check research statusnotebooklm research wait - wait for research (in subagent context)notebooklm use <id> - set context (⚠️ SINGLE-AGENT ONLY - use -n flag in parallel workflows)notebooklm create - create notebooknotebooklm ask "..." - chat queries (without --save-as-note)notebooklm history - display conversation history (read-only)notebooklm source add - add sourcesnotebooklm profile list - list profilesnotebooklm profile create - create profilenotebooklm profile switch - switch active profilenotebooklm doctor - check environment healthAsk before running:
notebooklm delete - destructivenotebooklm generate * - long-running, may failnotebooklm download * - writes to filesystemnotebooklm artifact wait - long-running (when in main conversation)notebooklm source wait - long-running (when in main conversation)notebooklm research wait - long-running (when in main conversation)notebooklm ask "..." --save-as-note - writes a notenotebooklm history --save - writes a note| Task | Command |
|---|---|
| Authenticate | notebooklm login |
| Diagnose auth issues | notebooklm auth check |
| Diagnose auth (full) | notebooklm auth check --test |
| List notebooks | notebooklm list |
| Create notebook | notebooklm create "Title" |
| Set context | notebooklm use <notebook_id> |
| Show context | notebooklm status |
| Add URL source | notebooklm source add "https://..." |
| Add file | notebooklm source add ./file.pdf |
| Add YouTube | notebooklm source add "https://youtube.com/..." |
| List sources | notebooklm source list |
| Delete source by ID | notebooklm source delete <source_id> |
| Delete source by exact title | notebooklm source delete-by-title "Exact Title" |
| Wait for source processing | notebooklm source wait <source_id> |
| Web research (fast) | notebooklm source add-research "query" |
| Web research (deep) | notebooklm source add-research "query" --mode deep --no-wait |
| Check research status | notebooklm research status |
| Wait for research | notebooklm research wait --import-all |
| Chat | notebooklm ask "question" |
| Chat (specific sources) | notebooklm ask "question" -s src_id1 -s src_id2 |
| Chat (with references) | notebooklm ask "question" --json |
| Chat (save answer as note) | notebooklm ask "question" --save-as-note |
| Chat (save with title) | notebooklm ask "question" --save-as-note --note-title "Title" |
| Show conversation history | notebooklm history |
| Save all history as note | notebooklm history --save |
| Continue specific conversation | notebooklm ask "question" -c <conversation_id> |
| Save history with title | notebooklm history --save --note-title "My Research" |
| Get source fulltext | notebooklm source fulltext <source_id> |
| Get source guide | notebooklm source guide <source_id> |
| Generate podcast | notebooklm generate audio "instructions" |
| Generate podcast (JSON) | notebooklm generate audio --json |
| Generate podcast (specific sources) | notebooklm generate audio -s src_id1 -s src_id2 |
| Generate video | notebooklm generate video "instructions" |
| Generate report | notebooklm generate report --format briefing-doc |
| Generate report (append instructions) | notebooklm generate report --format study-guide --append "Target audience: beginners" |
| Generate quiz | notebooklm generate quiz |
| Revise a slide | notebooklm generate revise-slide "prompt" --artifact <id> --slide 0 |
| Check artifact status | notebooklm artifact list |
| Wait for completion | notebooklm artifact wait <artifact_id> |
| Download audio | notebooklm download audio ./output.mp3 |
| Download video | notebooklm download video ./output.mp4 |
| Download slide deck (PDF) | notebooklm download slide-deck ./slides.pdf |
| Download slide deck (PPTX) | notebooklm download slide-deck ./slides.pptx --format pptx |
| Download report | notebooklm download report ./report.md |
| Download mind map | notebooklm download mind-map ./map.json |
| Download data table | notebooklm download data-table ./data.csv |
| Download quiz | notebooklm download quiz quiz.json |
| Download quiz (markdown) | notebooklm download quiz --format markdown quiz.md |
| Download flashcards | notebooklm download flashcards cards.json |
| Download flashcards (markdown) | notebooklm download flashcards --format markdown cards.md |
| Delete notebook | notebooklm notebook delete <id> |
| List languages | notebooklm language list |
| Get language | notebooklm language get |
| Set language | notebooklm language set zh_Hans |
| List profiles | notebooklm profile list |
| Create profile | notebooklm profile create work |
| Switch profile | notebooklm profile switch work |
| Delete profile | notebooklm profile delete old |
| Rename profile | notebooklm profile rename old new |
| Use profile (one-off) | notebooklm -p work list |
| Health check | notebooklm doctor |
| Health check (auto-fix) | notebooklm doctor --fix |
Parallel safety: Use explicit notebook IDs in parallel workflows. Commands supporting -n shorthand: artifact wait, source wait, research wait/status, download *. Download commands also support -a/--artifact. Other commands use --notebook. For chat, use -c <conversation_id> to target a specific conversation.
Partial IDs: Use first 6+ characters of UUIDs. Must be unique prefix (fails if ambiguous). Works for ID-based commands such as use, source delete, and wait. For exact source-title deletion, use source delete-by-title "Title". For automation, prefer full UUIDs to avoid ambiguity.
Commands with --json return structured data for parsing:
Create notebook:
$ notebooklm create "Research" --json
{"id": "abc123de-...", "title": "Research"}
Add source:
$ notebooklm source add "https://example.com" --json
{"source_id": "def456...", "title": "Example", "status": "processing"}
Generate artifact:
$ notebooklm generate audio "Focus on key points" --json
{"task_id": "xyz789...", "status": "pending"}
Chat with references:
$ notebooklm ask "What is X?" --json
{"answer": "X is... [1] [2]", "conversation_id": "...", "turn_number": 1, "is_follow_up": false, "references": [{"source_id": "abc123...", "citation_number": 1, "cited_text": "Relevant passage from source..."}, {"source_id": "def456...", "citation_number": 2, "cited_text": "Another passage..."}]}
Source fulltext (get indexed content):
$ notebooklm source fulltext <source_id> --json
{"source_id": "...", "title": "...", "char_count": 12345, "content": "Full indexed text..."}
Understanding citations: The cited_text in references is often a snippet or section header, not the full quoted passage. The start_char/end_char positions reference NotebookLM's internal chunked index, not the raw fulltext. Use SourceFulltext.find_citation_context() to locate citations:
fulltext = await client.sources.get_fulltext(notebook_id, ref.source_id)
matches = fulltext.find_citation_context(ref.cited_text) # Returns list[(context, position)]
if matches:
context, pos = matches[0] # First match; check len(matches) > 1 for duplicates
Extract IDs: Parse the id, source_id, or task_id field from JSON output.
All generate commands support:
-s, --source to use specific source(s) instead of all sources--language to set output language (defaults to configured language or 'en')--json for machine-readable output (returns task_id and status)--retry N to automatically retry on rate limits with exponential backoff| Type | Command | Options | Download |
|---|---|---|---|
| Podcast | generate audio |
--format [deep-dive|brief|critique|debate], --length [short|default|long] |
.mp3 |
| Video | generate video |
--format [explainer|brief], --style [auto|classic|whiteboard|kawaii|anime|watercolor|retro-print|heritage|paper-craft] |
.mp4 |
| Slide Deck | generate slide-deck |
--format [detailed|presenter], --length [default|short] |
.pdf / .pptx |
| Slide Revision | generate revise-slide "prompt" --artifact <id> --slide N |
--wait, --notebook |
(re-downloads parent deck) |
| Infographic | generate infographic |
--orientation [landscape|portrait|square], --detail [concise|standard|detailed], --style [auto|sketch-note|professional|bento-grid|editorial|instructional|bricks|clay|anime|kawaii|scientific] |
.png |
| Report | generate report |
--format [briefing-doc|study-guide|blog-post|custom], --append "extra instructions" |
.md |
| Mind Map | generate mind-map |
(sync, instant) | .json |
| Data Table | generate data-table |
description required | .csv |
| Quiz | generate quiz |
--difficulty [easy|medium|hard], --quantity [fewer|standard|more] |
.json/.md/.html |
| Flashcards | generate flashcards |
--difficulty [easy|medium|hard], --quantity [fewer|standard|more] |
.json/.md/.html |
These capabilities are available via CLI but not in NotebookLM's web interface:
| Feature | Command | Description |
|---|---|---|
| Batch downloads | download <type> --all |
Download all artifacts of a type at once |
| Quiz/Flashcard export | download quiz --format json |
Export as JSON, Markdown, or HTML (web UI only shows interactive view) |
| Mind map extraction | download mind-map |
Export hierarchical JSON for visualization tools |
| Data table export | download data-table |
Download structured tables as CSV |
| Slide deck as PPTX | download slide-deck --format pptx |
Download slide deck as editable .pptx (web UI only offers PDF) |
| Slide revision | generate revise-slide "prompt" --artifact <id> --slide N |
Modify individual slides with a natural-language prompt |
| Report template append | generate report --format study-guide --append "..." |
Append custom instructions to built-in format templates without losing the format type |
| Source fulltext | source fulltext <id> |
Retrieve the indexed text content of any source |
| Save chat to note | ask "..." --save-as-note / history --save |
Save Q&A answers or conversation history as notebook notes |
| Programmatic sharing | share commands |
Manage sharing permissions without the UI |
Time: 5-10 minutes total
notebooklm create "Research: [topic]" — if fails: check auth with notebooklm loginMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
notebooklm reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: notebooklm is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: notebooklm is focused, and the summary matches what you get after install.
I recommend notebooklm for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
notebooklm has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in notebooklm — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
notebooklm has been reliable in day-to-day use. Documentation quality is above average for community skills.
notebooklm is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
notebooklm reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for notebooklm matched our evaluation — installs cleanly and behaves as described in the markdown.
showing 1-10 of 36