NotebookLM Second Brain

Policy: Query the relevant NotebookLM notebook before web search or dumping full docs into context.

Description

This skill enforces a "Notebook First" retrieval policy. Instead of loading entire markdown files or running web searches for architecture decisions, debugging patterns, or security knowledge, the agent queries purpose-built NotebookLM notebooks via the nlm CLI. This keeps the agent context window lean and retrieval fast.

When to Apply

Scenario	Notebook	Why
"How does auth work?"	`project_sot`	Architecture decisions live here
"Why is this test failing?"	`debug_kb`	Error patterns and debugging playbooks
"Is this input sanitised?"	`security_handbook`	OWASP patterns and security reviews
"Explain the codebase"	`repo_onboarding`	Codebase atlas and mind maps
After successful build/verify	`project_sot`	Auto-sync implementation notes

Core Directives

1. Notebook ID Location

All notebook IDs are stored in .claude/notebooklm/notebooks.json. Never hard-code or fabricate IDs.

# Read current notebook config
cat .claude/notebooklm/notebooks.json

2. Notebook Routing

Query Type	Target Notebook	Fallback
Architecture, feature specs, implementation history	`project_sot`	Read CLAUDE.md directly
Error patterns, test failures, debugging steps	`debug_kb`	Search codebase with grep
OWASP, auth patterns, security reviews	`security_handbook`	Web search security docs
"How does X work?", codebase overview, onboarding	`repo_onboarding`	Read source files directly

3. CLI Command Reference

# Authentication
nlm login                              # Browser cookie extraction (one-time)
nlm login --check                      # Verify auth status

# Notebook management
nlm notebook list                      # List all notebooks
nlm notebook create "Name"             # Create new notebook
nlm notebook query <notebook_id>       # Interactive query

# Source management
nlm source add <notebook_id> --file <path>    # Add file source
nlm source add <notebook_id> --url <url>      # Add URL source
nlm source add <notebook_id> --text "content" # Add text source
nlm source list <notebook_id>                 # List sources

# Notes and audio
nlm note create <notebook_id> "Title"         # Create note
nlm audio create <notebook_id> --confirm      # Generate audio overview

4. Deterministic Routine

When setting up a new notebook:

Create — nlm notebook create "Name"
Add sources — Upload relevant files and URLs
Query — Verify the notebook returns useful answers
Export — Save notebook ID to notebooks.json

5. Post-Build Sync

After successful pnpm run verify or pnpm build, the sync hook (.claude/hooks/scripts/notebooklm-sync.ps1) automatically creates an implementation note in project_sot with:

Commit message and hash
Changed files list
Test results summary
Detected TODO items

Anti-Patterns

Never fabricate notebook IDs — only use IDs from notebooks.json (populated by /notebooklm-bootstrap)
Never dump full docs into context when a notebook query would suffice
Never skip the notebook and go straight to web search for project-specific knowledge
Never hard-code notebook IDs in scripts or commands — always read from config

Integration Points

System	Integration
Beads	Sync completed Beads tasks as implementation notes
Council of Logic	Architecture queries route through `project_sot` first
Hooks	Post-verify sync hook adds notes automatically
Skills	Other skills can query notebooks for domain knowledge

Setup

Run the bootstrap command to install, authenticate, and create all notebooks:

/notebooklm-bootstrap

This installs notebooklm-mcp-cli, authenticates via browser, creates the 4 notebooks, seeds them with project sources, and writes IDs to notebooks.json.

Validation

python scripts/validate-notebooks.py              # Schema validation
python scripts/validate-notebooks.py --check-ids   # Verify IDs populated
python scripts/validate-notebooks.py --dry-run-sync # Preview sync note

notebooklm-second-brain