notebooklm-research

description: "Topic-based research library via Google NotebookLM MCP. Query curated domain notebooks for market data, tech best practices, and industry patterns. Three modes: QUERY (ask questions across notebooks), CURATE (add sources, create/tag notebooks), AUDIT (check source counts, surface stale notebooks). All operations use mcp__notebooklm-mcp__* MCP tools — no CLI. Registry-first: every operation starts by reading {agency-root}/memory/notebooklm-registry.md, if it exists."

{agency-root} resolves to $AGENCY_HOME, else $CLAUDE_CONFIG_DIR, else the default Claude Code config directory — see docs/HOOKS.md for the exact resolution order.

Activation

Explicit: User says "/notebooklm-memory", "/notebooklm-research", "query research notebooks", "add source to notebook", "create a research notebook"

Intent detection:

• "What does the research say about Vietnamese SMEs?"
• "Look up AI agent patterns in the notebooks"
• "Add this URL to the market research notebook"
• "Create a new research notebook for fintech"
• "How many sources are in the market notebook?"
• "What do we know about Supabase best practices?"

Prerequisites

• NotebookLM MCP server running (mcp__notebooklm-mcp__* tools available)
• Authenticated via Google OAuth (your Google account)
• Registry at {agency-root}/memory/notebooklm-registry.md, if it exists (operator-accumulated — no template ships)

Mode 1: QUERY — Ask Questions

Query curated research notebooks for grounded answers with citations.

Single Notebook Query

1. Read {agency-root}/memory/notebooklm-registry.md (if it exists) to find the notebook slug and ID
2. Call mcp__notebooklm-mcp__notebook_query with the notebook ID and question
3. Return the answer with source citations

Cross-Notebook Query

For questions spanning multiple domains:

1. By tag: mcp__notebooklm-mcp__cross_notebook_query(tags=["vietnam", "sme"], query="...")
2. All notebooks: mcp__notebooklm-mcp__cross_notebook_query(all=true, query="...")

Query Tips

• Narrow queries outperform broad ones (NotebookLM uses RAG, not full re-read)
• Ask for citations: "Quote the exact sentence and cite the source"
• Ask for contradictions: "Do any sources disagree on this?"
• Ask for gaps: "What's missing from these sources on this topic?"

Mode 2: CURATE — Manage Sources & Notebooks

Add a Source

1. Read registry to get the notebook ID for the target slug
2. Check current source count (call mcp__notebooklm-mcp__notebook_describe or check registry)
3. If source count >= 45: warn the user and suggest archiving old sources first
4. Add the source:
   • URL: mcp__notebooklm-mcp__source_add(source_type="url", url="https://...")
   • Text: mcp__notebooklm-mcp__source_add(source_type="text", text="...")
   • Drive: mcp__notebooklm-mcp__source_add(source_type="drive", document_id="...")
   • File: mcp__notebooklm-mcp__source_add(source_type="file", file_path="...")
5. Update the source count in notebooklm-registry.md

Create a New Notebook

1. mcp__notebooklm-mcp__notebook_create(title="[CATEGORY] Full Title")
   • Use prefix convention: [MARKET], [TECH], [SALES], [CONTENT], [AI], [OPS]
2. Tag it: mcp__notebooklm-mcp__tag(action="add", tags=["tag1", "tag2"])
3. Seed with 5-10 initial sources (URL preferred)
4. Add entry to {agency-root}/memory/notebooklm-registry.md (create the file if it doesn't exist yet):
   • slug, notebook_id, title, tags, source count, project dependencies
5. Update Last updated date in registry

Source Selection Guidelines

Priority	Source Type	Example
Highest	Industry reports, government data (URL)	GSO Vietnam, e-Conomy SEA report
High	Official documentation (URL)	Next.js docs, Supabase docs
High	Research papers, whitepapers (URL)	Academic papers, policy documents
Medium	Curated blog posts, case studies (URL)	Vetted quality articles
Medium	Internal synthesis docs (text)	Audience profiles, research summaries
Avoid	Session logs, decisions.md, code files	These belong in the wiki (memory files) or the repo

Mode 3: AUDIT — Check Notebook Health

Quick Health Check

1. Read {agency-root}/memory/notebooklm-registry.md, if it exists
2. For each active notebook:
   • Call mcp__notebooklm-mcp__notebook_describe to verify it exists and get current state
   • Compare source count against the 45-source soft limit
   • Flag notebooks approaching the limit
3. Report: slug, title, source count, status (healthy / near-limit / stale)

Source Freshness Audit

1. For each notebook, call mcp__notebooklm-mcp__source_add with source_type="list" or check source metadata
2. Flag sources older than the notebook's refresh cadence:
   • AI/ML notebooks: monthly refresh
   • Market notebooks: quarterly refresh
   • Tech stack notebooks: semi-annual refresh
3. Recommend: which sources to refresh (re-add URL) or archive

Integration with Direct Lookups

Agents query NotebookLM for research-topic questions only, after the wiki and a shared-memory MCP server (if you run one) miss (order: wiki -> shared-memory MCP server -> NotebookLM; the curator agent was retired 2026-10-12). For a domain-level question (market research, tech best practices, industry patterns), the asking agent, or the one read-only general-purpose (sonnet) synthesis spawn it routes like any spawn:

1. Reads the registry to find relevant notebooks
2. Matches question domain to notebook tags
3. Queries via mcp__notebooklm-mcp__notebook_query
4. Returns answer with NotebookLM source citations

This skill covers human-invoked operations and direct agent lookups.

Autonomy Rules

Auto-approve (no confirmation needed):

• notebook_query, cross_notebook_query — reads
• notebook_list, notebook_describe — reads
• notebook_get — reads
• source_describe, source_get_content — reads
• tag(action="list") — reads
• Reading notebooklm-registry.md — reads

Require user confirmation:

• notebook_create — creates new notebook
• source_add — modifies notebook content
• notebook_delete — destructive
• source_delete — destructive
• tag(action="add"), tag(action="remove") — modifies organization
• studio_create — long-running generation
• notebook_share_* — exposes content externally

Relationship to Other Systems

NotebookLM = research only. It is NOT a memory or lookup layer.

Need	Where	Rule
Claude-only memory (prefs, lessons, project notes)	Wiki: MEMORY.md + memory files + project memory/	Always first
Cross-agent facts, handoffs, task board	A shared-memory MCP server, if you run one	Second
Research topics (markets, tech, industry)	NotebookLM	Last, research topics only
Code relationships	graphify / tokensave, on demand	Not a lookup step

Pinecone is retired as a lookup step (2026-10-08).