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>
3.3 KiB
3.3 KiB
name, description
| name | description |
|---|---|
| notebooklm-research | 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
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
# 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
# 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
# Check ongoing research
notebooklm research status
# Wait for completion
notebooklm research wait
notebooklm research wait --import-all # Auto-import found sources
Source Content Extraction
# 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
# 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:
# 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 statusnotebooklm source listnotebooklm source fulltextnotebooklm source guide
Ask first:
notebooklm source add-research(modifies notebook)notebooklm research wait --import-all(long-running)
Tips
- Use deep mode for comprehensive research
- Use --no-wait for non-blocking operations
- Spawn subagent for long waits
- 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 |