Agent skill
notebook-lm-research
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.
Install this agent skill to your Project
npx add-skill https://github.com/CleanExpo/ATO/tree/main/.agent/skills/notebook_lm_research
SKILL.md
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
- Source Quality: Prioritize authoritative sources (academic, official, expert)
- Citation Precision: Always include page numbers and direct quotes
- Bias Detection: Flag potential biases in source materials
- 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
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