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refactor(skills): clean skill names (strip NN- prefix from name:) — convention change

Adopt: directory keeps its NN- ordering prefix; skill `name:` is the clean form
without it (dir 16-seo-schema-validator → name: seo-schema-validator). Nicer to
invoke, matches the original desktop/SKILL.md names, still globally unique.

- 71 root SKILL.md: name: NN-foo → name: foo (flat skills + reference-curator suite).
  Plugins (mac-optimizer/multi-agent-guide/dintel-bootstrap) already clean; 95 already clean.
- scripts/migrate_skill_root.py: derive name = dirname minus NN- prefix (skill_name()).
- CLAUDE.md + SKILL-MIGRATION-GUIDE.md: document the dir-prefix / clean-name convention.

verify_skills.py: 0 name collisions across all renamed skills. (The ~/.claude/skills
symlinks were re-pointed to the clean names separately — filesystem only.)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-05-28 02:11:01 +09:00

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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 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

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

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