Flatline Knowledge Skill

Purpose

Provides optional NotebookLM integration for the Flatline Protocol, enabling external knowledge retrieval from curated AI-powered notebooks.

Overview

This skill automates browser interaction with Google NotebookLM to query organizational knowledge bases. It serves as a Tier 2 knowledge source, supplementing the local grimoire search (Tier 1).

Architecture

Flatline Protocol
       │
       ▼
┌─────────────────┐
│ Knowledge Hub   │
├─────────────────┤
│ Tier 1: Local   │◄── Framework learnings, project context
│ Weight: 1.0     │    (always available)
├─────────────────┤
│ Tier 2: NLML    │◄── NotebookLM curated sources
│ Weight: 0.8     │    (this skill, optional)
└─────────────────┘

Prerequisites

1. Python 3.10+ with Patchright installed
2. Chromium browser available on PATH
3. Google account with NotebookLM access
4. Initial authentication completed (one-time setup)

Workflow

1. Check Availability

# Check if NotebookLM is configured and authenticated
if not config.notebooklm.enabled:
    return {"status": "disabled", "results": []}

if not auth_session_valid():
    warn("NotebookLM session expired. Using local knowledge only.")
    return {"status": "auth_expired", "results": []}

2. Query NotebookLM

# Launch browser with persistent session
async with patchright.async_playwright() as p:
    browser = await p.chromium.launch_persistent_context(
        user_data_dir="~/.claude/notebooklm-auth/",
        headless=True
    )

    # Navigate to notebook
    page = await browser.new_page()
    await page.goto(f"https://notebooklm.google.com/notebook/{notebook_id}")

    # Submit query
    query = f"{domain} {phase} best practices"
    await page.fill("textarea[aria-label='Ask']", query)
    await page.click("button[aria-label='Submit']")

    # Wait for response
    await page.wait_for_selector(".response-content", timeout=30000)

    # Extract results
    response = await page.text_content(".response-content")
    citations = await page.query_selector_all(".citation")

3. Format Results

# Return structured knowledge
return {
    "status": "success",
    "results": [
        {
            "content": response,
            "citations": [c.text for c in citations],
            "source": "notebooklm",
            "weight": 0.8,
            "latency_ms": elapsed
        }
    ]
}

Error Handling

Scenario	Behavior	User Impact
NotebookLM disabled	Skip gracefully	None (silent)
Auth expired	Warn, fallback to local	Warning message
Timeout (>30s)	Warn, fallback to local	Warning message
Browser unavailable	Warn, fallback to local	Warning message
Network error	Warn, fallback to local	Warning message

Critical: This skill NEVER blocks the Flatline Protocol workflow. All failures result in graceful fallback to local knowledge.

Configuration

In .loa.config.yaml:

flatline_protocol:
  knowledge:
    notebooklm:
      enabled: false  # Disabled by default
      notebook_id: "your-notebook-id"
      timeout_ms: 30000
      headless: true

Authentication Setup

See resources/auth-setup.md for detailed instructions.

Quick start:

1. Run python resources/notebooklm-query.py --setup-auth
2. Complete Google sign-in in the browser window
3. Session is saved to ~/.claude/notebooklm-auth/

Usage

From Orchestrator

The orchestrator calls this skill automatically when:

• flatline_protocol.knowledge.notebooklm.enabled: true
• Local knowledge retrieval completes

Manual Testing

# Dry run (no browser)
python resources/notebooklm-query.py --domain "security" --phase prd --dry-run

# With authentication
python resources/notebooklm-query.py --domain "crypto wallet" --phase sdd --notebook "loa-learnings"

# Setup authentication
python resources/notebooklm-query.py --setup-auth

Integration Points

Input (from Flatline Orchestrator)

{
  "domain": "crypto wallet authentication",
  "phase": "prd",
  "notebook_id": "abc123",
  "timeout_ms": 30000
}

Output (to Flatline Orchestrator)

{
  "status": "success",
  "results": [
    {
      "content": "Key considerations for crypto wallet PRDs include...",
      "citations": ["Source 1", "Source 2"],
      "source": "notebooklm",
      "weight": 0.8
    }
  ],
  "latency_ms": 5234
}

Metrics

Metric	Target	Measurement
Latency P50	<10s	From query submit to response
Latency P95	<25s	Browser automation overhead
Success rate	>90%	When enabled and authenticated
Timeout rate	<5%	Queries exceeding 30s

Privacy Considerations

• Requires Google account authentication
• Queries are sent to Google NotebookLM service
• Session data stored locally in ~/.claude/notebooklm-auth/
• No query logging by default (configurable)

Troubleshooting

Common Issues

"Auth session expired"

• Re-run --setup-auth to refresh authentication

"Browser not found"

• Ensure Chromium is installed: which chromium
• Or install: apt install chromium / brew install chromium

"Timeout waiting for response"

• Check NotebookLM service status
• Increase timeout in config
• Network latency may exceed 30s for complex queries

"Module patchright not found"

• Install: pip install patchright
• Ensure correct Python environment is active

Resources

• resources/notebooklm-query.py - Browser automation script
• resources/requirements.txt - Python dependencies
• resources/auth-setup.md - Authentication documentation