feat: Add NotebookLM skills (50-53) for Claude Code and Desktop

Add 4 specialized NotebookLM skills based on notebooklm-py library:

- 50-notebooklm-agent: Q&A agent for notebook queries with citations
- 51-notebooklm-automation: Full notebook/source/artifact management
- 52-notebooklm-studio: Content generation (podcasts, videos, quizzes)
- 53-notebooklm-research: Web/Drive research and source discovery

Each skill includes:
- README.md: Overview and quick start
- code/CLAUDE.md: Claude Code version (concise)
- desktop/SKILL.md: Claude Desktop version (with YAML frontmatter)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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2026-02-03 19:07:00 +07:00
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# NotebookLM Agent
Q&A agent that answers user questions based on NotebookLM notebooks. Leverages NotebookLM's Gemini-powered analysis to provide grounded, citation-backed responses from uploaded sources.
## Use Cases
- Ask questions about documents in a specific notebook
- Get summaries with source citations
- Compare information across multiple sources
- Research assistant workflows
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login # One-time browser auth
```
## Quick Start
```bash
# Set active notebook
notebooklm use <notebook_id>
# Ask questions
notebooklm ask "What are the key findings?"
notebooklm ask "Compare approaches from different sources"
# Get citations with JSON output
notebooklm ask "Summarize the methodology" --json
```
## Versions
| Version | Path | Purpose |
|---------|------|---------|
| Claude Code | `code/` | CLAUDE.md for Claude Code integration |
| Claude Desktop | `desktop/` | SKILL.md for Claude Desktop skills |
## Related Skills
- [51-notebooklm-automation](../51-notebooklm-automation/) - Full automation workflows
- [52-notebooklm-studio](../52-notebooklm-studio/) - Content generation (podcasts, videos)
- [53-notebooklm-research](../53-notebooklm-research/) - Research and source discovery

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# NotebookLM Agent - Claude Code
Q&A agent that answers questions using NotebookLM's Gemini-powered analysis with source citations.
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login # One-time auth
```
## Commands
```bash
# List notebooks
notebooklm list
# Set context
notebooklm use <notebook_id>
# Ask questions
notebooklm ask "What are the key findings?"
notebooklm ask "Elaborate on point 2" # continues conversation
notebooklm ask "New topic" --new # new conversation
# With citations (JSON output)
notebooklm ask "Summarize" --json
# Query specific sources
notebooklm ask "Compare" -s source1 -s source2
```
## Autonomy
**Auto-run:** `list`, `status`, `source list`, `ask`
**Ask first:** `delete`, `source add`
## JSON Output Format
```json
{
"answer": "Response with [1] [2] citations",
"references": [
{"source_id": "...", "citation_number": 1, "cited_text": "..."}
]
}
```
## Error Recovery
| Error | Fix |
|-------|-----|
| No context | `notebooklm use <id>` |
| Auth error | `notebooklm login` |

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---
name: notebooklm-agent
description: |
Q&A agent for NotebookLM notebooks. Ask questions and get grounded, citation-backed answers from your sources.
Triggers: ask NotebookLM, query notebook, research question, 노트북 질문, NotebookLM 에이전트.
---
# NotebookLM Agent
Q&A agent that answers questions using NotebookLM's Gemini-powered analysis. Returns grounded responses with source citations.
## Prerequisites
NotebookLM CLI must be installed and authenticated:
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## When This Skill Activates
- User asks "ask NotebookLM about X"
- User wants to "query my notebook"
- User needs "research answers from sources"
- Korean: "노트북LM에서 찾아줘", "노트북 질문"
## Quick Reference
| Task | Command |
|------|---------|
| List notebooks | `notebooklm list` |
| Set active notebook | `notebooklm use <id>` |
| Ask question | `notebooklm ask "question"` |
| New conversation | `notebooklm ask "question" --new` |
| With citations | `notebooklm ask "question" --json` |
| Specific sources | `notebooklm ask "q" -s src1 -s src2` |
## Workflow
### 1. Select Notebook
```bash
# List available notebooks
notebooklm list
# Set context (use partial ID)
notebooklm use abc123
```
### 2. Ask Questions
```bash
# Simple question
notebooklm ask "What are the main findings?"
# Follow-up (continues conversation)
notebooklm ask "Can you elaborate on point 2?"
# New conversation
notebooklm ask "Different topic" --new
# Query specific sources only
notebooklm ask "Compare these two" -s source1_id -s source2_id
```
### 3. Get Structured Output
For citations and references, use `--json`:
```bash
notebooklm ask "Summarize the methodology" --json
```
Returns:
```json
{
"answer": "The methodology involves... [1] [2]",
"references": [
{"source_id": "abc...", "citation_number": 1, "cited_text": "..."},
{"source_id": "def...", "citation_number": 2, "cited_text": "..."}
]
}
```
## Autonomy Rules
**Run automatically:**
- `notebooklm list` - view notebooks
- `notebooklm status` - check context
- `notebooklm source list` - view sources
- `notebooklm ask "..."` - answer questions
**Ask before running:**
- `notebooklm delete` - destructive operations
- `notebooklm source add` - modifies notebook
## Tips
1. **Set context first**: Always `use` a notebook before asking
2. **Use --json for citations**: Get structured references for research
3. **Continue conversations**: Omit `--new` for follow-up questions
4. **Filter sources**: Use `-s` to query specific documents only
## Error Handling
| Error | Solution |
|-------|----------|
| "No notebook context" | Run `notebooklm use <id>` |
| Auth error | Run `notebooklm login` |
| Source not found | Check `notebooklm source list` |
## Related Skills
- **notebooklm-automation**: Full notebook management
- **notebooklm-studio**: Generate podcasts, videos, quizzes
- **notebooklm-research**: Add sources and research workflows

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# NotebookLM Automation
Complete automation toolkit for NotebookLM operations. Manage notebooks, sources, and artifacts programmatically.
## Use Cases
- Batch notebook management
- Automated source ingestion
- CI/CD integration for documentation
- Multi-account workflows
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## Quick Start
```bash
# Notebook management
notebooklm create "Project Research"
notebooklm list --json
notebooklm rename <id> "New Name"
notebooklm delete <id>
# Source management
notebooklm source add "https://example.com"
notebooklm source add ./document.pdf
notebooklm source list --json
```
## Versions
| Version | Path | Purpose |
|---------|------|---------|
| Claude Code | `code/` | CLAUDE.md for Claude Code |
| Claude Desktop | `desktop/` | SKILL.md for Claude Desktop |
## Related Skills
- [50-notebooklm-agent](../50-notebooklm-agent/) - Q&A agent
- [52-notebooklm-studio](../52-notebooklm-studio/) - Content generation
- [53-notebooklm-research](../53-notebooklm-research/) - Research workflows

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# NotebookLM Automation - Claude Code
Complete programmatic control over NotebookLM notebooks, sources, and artifacts.
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## Commands
### Notebooks
```bash
notebooklm list [--json]
notebooklm create "Title" [--json]
notebooklm rename <id> "New Name"
notebooklm delete <id>
notebooklm use <id>
```
### Sources
```bash
notebooklm source add "https://..." [--json]
notebooklm source add ./file.pdf
notebooklm source list [--json]
notebooklm source delete <id>
notebooklm source wait <id>
```
### Artifacts
```bash
notebooklm artifact list [--json]
notebooklm artifact wait <id>
notebooklm artifact delete <id>
```
## Environment Variables
| Variable | Purpose |
|----------|---------|
| `NOTEBOOKLM_HOME` | Custom config dir |
| `NOTEBOOKLM_AUTH_JSON` | Inline auth (CI/CD) |
## Autonomy
**Auto-run:** `list`, `status`, `create`, `use`, `source add`
**Ask first:** `delete`, `rename`

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---
name: notebooklm-automation
description: |
Complete NotebookLM automation for notebooks, sources, and artifacts management.
Triggers: manage NotebookLM, create notebook, add sources, 노트북 관리, NotebookLM 자동화.
---
# NotebookLM Automation
Complete programmatic control over NotebookLM notebooks, sources, and artifacts.
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## When This Skill Activates
- "Create a NotebookLM notebook"
- "Add sources to NotebookLM"
- "Manage my notebooks"
- Korean: "노트북 만들어줘", "소스 추가"
## Quick Reference
### Notebook Operations
| Task | Command |
|------|---------|
| List all | `notebooklm list` |
| List (JSON) | `notebooklm list --json` |
| Create | `notebooklm create "Title"` |
| Rename | `notebooklm rename <id> "New"` |
| Delete | `notebooklm delete <id>` |
| Set context | `notebooklm use <id>` |
### Source Operations
| Task | Command |
|------|---------|
| Add URL | `notebooklm source add "https://..."` |
| Add file | `notebooklm source add ./file.pdf` |
| Add YouTube | `notebooklm source add "youtube.com/..."` |
| List sources | `notebooklm source list` |
| Delete source | `notebooklm source delete <id>` |
| Wait for ready | `notebooklm source wait <id>` |
### Artifact Operations
| Task | Command |
|------|---------|
| List artifacts | `notebooklm artifact list` |
| Wait for completion | `notebooklm artifact wait <id>` |
| Delete artifact | `notebooklm artifact delete <id>` |
## Workflows
### Bulk Import Sources
```bash
notebooklm create "Research Collection"
notebooklm source add "https://url1.com"
notebooklm source add "https://url2.com"
notebooklm source add ./local.pdf
notebooklm source list
```
### CI/CD Integration
Use `--json` for machine-readable output:
```bash
# Create and capture ID
NOTEBOOK_ID=$(notebooklm create "Docs" --json | jq -r '.id')
# Add sources
notebooklm source add "https://docs.example.com" --json
# Export for downstream processing
notebooklm list --json > notebooks.json
```
## Environment Variables
| Variable | Purpose |
|----------|---------|
| `NOTEBOOKLM_HOME` | Custom config directory |
| `NOTEBOOKLM_AUTH_JSON` | Inline auth (CI/CD) |
## Autonomy Rules
**Auto-run:** `list`, `status`, `source list`, `artifact list`, `create`, `use`
**Ask first:** `delete`, `rename`
## Error Handling
| Error | Solution |
|-------|----------|
| Auth error | `notebooklm login` |
| No context | `notebooklm use <id>` |
| Rate limit | Wait 5-10 min, retry |

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# NotebookLM Studio
Content generation toolkit for NotebookLM Studio artifacts. Create podcasts, videos, quizzes, flashcards, slide decks, infographics, and more.
## Use Cases
- Generate audio overviews (podcasts) from sources
- Create educational videos with multiple styles
- Build quizzes and flashcards for learning
- Export mind maps and data tables
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## Quick Start
```bash
# Generate content
notebooklm generate audio "Focus on key findings"
notebooklm generate video --style whiteboard
notebooklm generate quiz --difficulty medium
notebooklm generate flashcards
# Download artifacts
notebooklm download audio ./podcast.mp3
notebooklm download video ./overview.mp4
notebooklm download quiz --format markdown ./quiz.md
```
## Content Types
| Type | Formats | Output |
|------|---------|--------|
| Audio | deep-dive, brief, critique, debate | MP3 |
| Video | 9 visual styles | MP4 |
| Quiz | configurable difficulty | JSON/MD/HTML |
| Flashcards | configurable quantity | JSON/MD/HTML |
| Slide Deck | detailed, presenter | PDF |
| Infographic | 3 orientations | PNG |
| Mind Map | hierarchical | JSON |
| Data Table | custom structure | CSV |
## Versions
| Version | Path | Purpose |
|---------|------|---------|
| Claude Code | `code/` | CLAUDE.md for Claude Code |
| Claude Desktop | `desktop/` | SKILL.md for Claude Desktop |
## Related Skills
- [50-notebooklm-agent](../50-notebooklm-agent/) - Q&A agent
- [51-notebooklm-automation](../51-notebooklm-automation/) - Notebook management
- [53-notebooklm-research](../53-notebooklm-research/) - Research workflows

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# NotebookLM Studio - Claude Code
Generate NotebookLM Studio content: audio, video, quizzes, flashcards, slides, infographics, mind maps.
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## Generate Commands
```bash
# Audio
notebooklm generate audio "instructions"
notebooklm generate audio --format debate --length longer
# Video
notebooklm generate video --style whiteboard
# Quiz & Flashcards
notebooklm generate quiz --difficulty hard
notebooklm generate flashcards --quantity more
# Visual
notebooklm generate slide-deck --format detailed
notebooklm generate infographic --orientation portrait
notebooklm generate mind-map
# Data
notebooklm generate data-table "description"
notebooklm generate report --format study_guide
```
## Download Commands
```bash
notebooklm artifact list # Check status
notebooklm download audio ./podcast.mp3
notebooklm download video ./video.mp4
notebooklm download quiz --format markdown ./quiz.md
notebooklm download flashcards --format json ./cards.json
notebooklm download slide-deck ./slides.pdf
notebooklm download mind-map ./mindmap.json
```
## Video Styles
`classic`, `whiteboard`, `kawaii`, `anime`, `pixel`, `watercolor`, `neon`, `paper`, `sketch`
## Audio Formats
`deep-dive`, `brief`, `critique`, `debate`
## Timing
| Type | Time |
|------|------|
| Mind map | Instant |
| Quiz | 5-15 min |
| Audio | 10-20 min |
| Video | 15-45 min |
## Autonomy
**Auto-run:** `artifact list`
**Ask first:** `generate *`, `download *`

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---
name: notebooklm-studio
description: |
Content generation for NotebookLM Studio artifacts - podcasts, videos, quizzes, flashcards, and more.
Triggers: create podcast, generate video, make quiz, 팟캐스트 만들기, 퀴즈 생성, NotebookLM 스튜디오.
---
# NotebookLM Studio
Generate all NotebookLM Studio content types: audio, video, quizzes, flashcards, slide decks, infographics, mind maps, and data tables.
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## When This Skill Activates
- "Create a podcast about my sources"
- "Generate a video explainer"
- "Make flashcards for studying"
- "Turn this into a quiz"
- Korean: "팟캐스트 만들어줘", "비디오 생성", "퀴즈 만들기"
## Content Types
| Type | Command | Options | Output |
|------|---------|---------|--------|
| **Audio** | `generate audio` | `--format`, `--length`, `--language` | MP3 |
| **Video** | `generate video` | `--style`, `--format` | MP4 |
| **Quiz** | `generate quiz` | `--difficulty`, `--quantity` | JSON/MD/HTML |
| **Flashcards** | `generate flashcards` | `--difficulty`, `--quantity` | JSON/MD/HTML |
| **Slide Deck** | `generate slide-deck` | `--format`, `--length` | PDF |
| **Infographic** | `generate infographic` | `--orientation`, `--detail` | PNG |
| **Mind Map** | `generate mind-map` | (instant) | JSON |
| **Data Table** | `generate data-table` | description required | CSV |
| **Report** | `generate report` | `--format` | Markdown |
## Quick Reference
### Generate Content
```bash
# Audio (podcast)
notebooklm generate audio "Focus on key findings"
notebooklm generate audio --format debate --length longer
# Video
notebooklm generate video --style whiteboard
notebooklm generate video --style anime "Make it fun"
# Quiz & Flashcards
notebooklm generate quiz --difficulty hard --quantity more
notebooklm generate flashcards --quantity standard
# Visual content
notebooklm generate slide-deck --format detailed
notebooklm generate infographic --orientation portrait
notebooklm generate mind-map
# Data extraction
notebooklm generate data-table "Compare all methods mentioned"
notebooklm generate report --format study_guide
```
### Download Artifacts
```bash
# Check status first
notebooklm artifact list
# Download when ready
notebooklm download audio ./podcast.mp3
notebooklm download video ./overview.mp4
notebooklm download quiz --format markdown ./quiz.md
notebooklm download flashcards --format json ./cards.json
notebooklm download slide-deck ./slides.pdf
notebooklm download infographic ./infographic.png
notebooklm download mind-map ./mindmap.json
notebooklm download data-table ./data.csv
```
## Video Styles
| Style | Description |
|-------|-------------|
| `classic` | Standard presentation |
| `whiteboard` | Hand-drawn whiteboard |
| `kawaii` | Cute animated style |
| `anime` | Japanese animation |
| `pixel` | 8-bit pixel art |
| `watercolor` | Painted aesthetic |
| `neon` | Glowing neon effects |
| `paper` | Paper cutout animation |
| `sketch` | Pencil sketch style |
## Audio Formats
| Format | Description |
|--------|-------------|
| `deep-dive` | Comprehensive exploration |
| `brief` | Quick summary |
| `critique` | Critical analysis |
| `debate` | Two-sided discussion |
## Processing Times
| Type | Typical Time | Timeout |
|------|--------------|---------|
| Mind map | Instant | - |
| Quiz/Flashcards | 5-15 min | 900s |
| Audio | 10-20 min | 1200s |
| Video | 15-45 min | 2700s |
## Autonomy Rules
**Auto-run:** `artifact list`, `artifact wait` (in subagent)
**Ask first:** `generate *`, `download *`
## Language Settings
```bash
notebooklm language list # Show 80+ languages
notebooklm language set ja # Japanese
notebooklm language set ko # Korean
notebooklm language set zh_Hans # Simplified Chinese
```
## Error Handling
| Error | Solution |
|-------|----------|
| Rate limited | Wait 5-10 min, retry |
| Generation failed | Check `artifact list`, retry later |
| Download fails | Ensure artifact status is `completed` |

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# NotebookLM Research
Research and source discovery toolkit for NotebookLM. Web research, Drive search, auto-import, and source text extraction.
## Use Cases
- Automated research on topics
- Web and Google Drive source discovery
- Source fulltext extraction
- Research pipeline automation
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## Quick Start
```bash
# Web research
notebooklm source add-research "topic query"
notebooklm source add-research "topic" --mode deep --import-all
# Drive research
notebooklm source add-research "topic" --from drive
# Extract source content
notebooklm source fulltext <source_id>
notebooklm source guide <source_id>
```
## Research Modes
| Mode | Sources | Time |
|------|---------|------|
| `fast` | 5-10 | seconds |
| `deep` | 20+ | 2-5 min |
## Versions
| Version | Path | Purpose |
|---------|------|---------|
| Claude Code | `code/` | CLAUDE.md for Claude Code |
| Claude Desktop | `desktop/` | SKILL.md for Claude Desktop |
## Related Skills
- [50-notebooklm-agent](../50-notebooklm-agent/) - Q&A agent
- [51-notebooklm-automation](../51-notebooklm-automation/) - Notebook management
- [52-notebooklm-studio](../52-notebooklm-studio/) - Content generation

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# NotebookLM Research - Claude Code
Research workflows: web research, Drive search, auto-import, source extraction.
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## Research Commands
```bash
# Web research
notebooklm source add-research "topic"
notebooklm source add-research "topic" --mode deep --import-all
notebooklm source add-research "topic" --mode deep --no-wait
# Drive research
notebooklm source add-research "topic" --from drive
# Status and wait
notebooklm research status
notebooklm research wait --import-all
```
## Source Extraction
```bash
notebooklm source fulltext <id>
notebooklm source guide <id>
```
## Research Modes
| Mode | Sources | Time |
|------|---------|------|
| `fast` | 5-10 | seconds |
| `deep` | 20+ | 2-5 min |
## Subagent Pattern
```python
# Non-blocking deep research
notebooklm source add-research "topic" --mode deep --no-wait
# Spawn subagent to wait
Task(
prompt="Wait for research and import: notebooklm research wait -n {id} --import-all",
subagent_type="general-purpose"
)
```
## Autonomy
**Auto-run:** `research status`, `source fulltext`, `source guide`
**Ask first:** `source add-research`, `research wait --import-all`

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---
name: notebooklm-research
description: |
Research and source discovery for NotebookLM. Web/Drive research, auto-import, and source text extraction.
Triggers: research topic, find sources, web research, 리서치, 자료 조사, NotebookLM 연구.
---
# NotebookLM Research
Research workflows for NotebookLM: web research, Drive search, auto-import, and source content extraction.
## Prerequisites
```bash
pip install notebooklm-py
playwright install chromium
notebooklm login
```
## When This Skill Activates
- "Research [topic] in NotebookLM"
- "Find sources about X"
- "Do web research on Y"
- "Search my Drive for documents"
- Korean: "리서치 해줘", "자료 찾아줘", "웹 검색"
## Research Modes
| Mode | Sources Found | Time | Use Case |
|------|---------------|------|----------|
| `fast` | 5-10 | seconds | Quick overview |
| `deep` | 20+ | 2-5 min | Comprehensive research |
## Quick Reference
### Web Research
```bash
# Fast research (default)
notebooklm source add-research "artificial intelligence trends"
# Deep research with auto-import
notebooklm source add-research "climate change policy" --mode deep --import-all
# Deep research (non-blocking, wait separately)
notebooklm source add-research "topic" --mode deep --no-wait
notebooklm research wait --import-all
```
### Drive Research
```bash
# Search Google Drive
notebooklm source add-research "quarterly report" --from drive
# Deep Drive search
notebooklm source add-research "project docs" --from drive --mode deep
```
### Research Status
```bash
# Check ongoing research
notebooklm research status
# Wait for completion
notebooklm research wait
notebooklm research wait --import-all # Auto-import found sources
```
## Source Content Extraction
```bash
# Get indexed fulltext
notebooklm source fulltext <source_id>
notebooklm source fulltext <source_id> --json
# Get AI-generated guide
notebooklm source guide <source_id>
```
## Workflow: Research to Analysis
```bash
# 1. Create notebook
notebooklm create "AI Research Project"
# 2. Run deep research
notebooklm source add-research "large language models 2024" --mode deep --no-wait
# 3. Wait and import (can spawn subagent for this)
notebooklm research wait --import-all
# 4. Verify sources
notebooklm source list
# 5. Start analysis
notebooklm ask "What are the key trends?"
```
## Subagent Pattern for Deep Research
For non-blocking deep research:
```python
# Main conversation
notebooklm source add-research "topic" --mode deep --no-wait
# Spawn subagent to wait
Task(
prompt="Wait for research in notebook {id} and import sources.
Use: notebooklm research wait -n {id} --import-all --timeout 300
Report how many sources were imported.",
subagent_type="general-purpose"
)
```
## Autonomy Rules
**Auto-run:**
- `notebooklm research status`
- `notebooklm source list`
- `notebooklm source fulltext`
- `notebooklm source guide`
**Ask first:**
- `notebooklm source add-research` (modifies notebook)
- `notebooklm research wait --import-all` (long-running)
## Tips
1. **Use deep mode** for comprehensive research
2. **Use --no-wait** for non-blocking operations
3. **Spawn subagent** for long waits
4. **Check research status** before importing
## Error Handling
| Error | Solution |
|-------|----------|
| No results | Try different keywords |
| Timeout | Extend timeout or check status |
| Rate limit | Wait and retry |