4.5 Library Management Best Practices

Organizing Notebooks

Naming conventions:

# Good: Descriptive, searchable
"LLM Engineer Handbook"
"Playwright Testing Guide"
"Next.js Architecture Patterns"

# Bad: Vague, unhelpful
"Notebook 1"
"My Docs"
"Tech Stuff"

Topics strategy:

# Specific, hierarchical
topics: ["RAG", "embeddings", "vector databases", "LLM fine-tuning"]

# Too broad
topics: ["AI", "programming"]

Use cases (helps Claude auto-select):

# Action-oriented
use_cases: [
  "When implementing RAG systems",
  "For fine-tuning LLM models",
  "To understand embeddings architecture"
]

Metadata Refinement Workflow

After using a notebook, refine its metadata:

# Initial add (minimal)
"Add notebook: <url>
Name: TypeScript Guide
Description: TypeScript best practices
Topics: TypeScript, types"

# After usage (refine)
"Update TypeScript Guide:
 - Add topic: generics
 - Add topic: utility types
 - Add use case: When designing type-safe APIs
 - Add tag: advanced"

Search and Discovery

Keyword search:

"Search library for: React hooks"
"Search library for: testing"
"Search library for: architecture patterns"

Smart selection (Claude decides):

"Which notebook should I consult about database design?"
# Claude searches library, proposes best match

"I need help with TypeScript generics"
# Claude auto-selects TypeScript Guide if metadata matches

Notebook Lifecycle

# 1. Add
"Add notebook: <url> - Name: X, Description: Y, Topics: Z"

# 2. Use
"In X notebook, ask: ..."

# 3. Refine
"Update X: Add topic: ..., Add use case: ..."

# 4. Archive (full profile)
"Remove notebook: X"  # If outdated or duplicate

Cost

Free: NotebookLM (including MCP integration) is free with Google account

Limits:

• Free tier: 100 notebooks, 50 sources per notebook, 500K words, 50 daily queries
• Google AI Premium/Ultra: 5x higher limits