notebook-lm-research

name	notebook-lm-research
description	Performs deep document analysis and research synthesis using NotebookLM for long-context document grounding. Enables multi-source research aggregation, citation extraction, and knowledge synthesis for content creation workflows.

NotebookLM Research Skill

Long-context document grounding and research synthesis capability powered by Google NotebookLM.

When to Use

Activate this skill when the task involves:

• Deep document analysis (PDFs, articles, reports)
• Multi-source research synthesis
• Citation extraction and verification
• Knowledge base building for content creation
• Literature review and summarization

Capabilities

1. Document Ingestion

Upload and process documents for analysis:

• Formats: PDF, Google Docs, web pages, text files
• Capacity: Up to 50 sources per notebook
• Context: 1M+ token window for comprehensive analysis

2. Research Synthesis

Extract and synthesize information:

• Key themes and patterns
• Contradictions and gaps
• Citation mapping
• Expert quotes and statistics

3. Query-Based Analysis

Answer specific research questions:

• Fact verification
• Comparative analysis
• Timeline construction
• Entity relationship mapping

Execution Pattern

1. INGEST → Add source documents to NotebookLM notebook
2. ANALYZE → Run initial summary and theme extraction
3. QUERY → Execute targeted research questions
4. SYNTHESIZE → Aggregate findings into structured output
5. CITE → Generate citation references for all claims

Output Format

Research outputs should follow this structure:

<research_output>
  <executive_summary>
    <!-- 2-3 paragraph overview -->
  </executive_summary>
  
  <key_findings>
    <finding source="[citation]" confidence="high|medium|low">
      <!-- Specific insight -->
    </finding>
  </key_findings>
  
  <themes>
    <theme name="Theme Name">
      <description><!-- Pattern description --></description>
      <sources><!-- List of supporting sources --></sources>
    </theme>
  </themes>
  
  <citations>
    <citation id="1" source="..." page="..." quote="..." />
  </citations>
</research_output>

Integration Points

• Content Orchestrator: Primary consumer for content creation workflows
• Google Slides Storyboard: Feeds research into presentation narratives
• GEO Marketing Agent: Provides citation vectors for authority scoring

Best Practices

1. Source Quality: Prioritize authoritative sources (academic, official, expert)
2. Citation Precision: Always include page numbers and direct quotes
3. Bias Detection: Flag potential biases in source materials
4. Freshness: Note publication dates for time-sensitive topics

Error Handling

Error	Recovery
Document upload fails	Retry with smaller chunks or alternative format
Context limit exceeded	Prioritize most relevant sources
No relevant findings	Expand search scope or reformulate queries

Cost Considerations

• Fuel Cost: 10-30 PTS per research session
• Optimization: Cache frequently accessed research for reuse