
Deep Research Notebooklm
- 9 installs
- 30.1k repo stars
- Updated August 4, 2026
- davila7/claude-code-templates
Conduct structured multi-source research using Google NotebookLM via MCP, then deliver formatted briefs and optional studio artifacts like slides and podcasts.
About
Runs a scoped research workflow through the NotebookLM MCP for market, competitive, prospect, and trend analysis, producing briefs plus optional artifacts. A developer uses it to research a topic deeply and generate slides, audio, videos, or reports.
- Research-type routing from market sizing to competitive intel
- Optional studio artifacts: slides, podcasts, videos, infographics, mind maps
Deep Research Notebooklm by the numbers
- 9 all-time installs (skills.sh)
- Ranked #12,152 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 9 |
|---|---|
| repo stars | ★ 30.1k |
| Last updated | August 4, 2026 |
| Repository | davila7/claude-code-templates ↗ |
What it does
Conduct structured multi-source research using Google NotebookLM via MCP, then deliver formatted briefs and optional studio artifacts like slides and podcasts.
Files
Deep Research via NotebookLM
Research $ARGUMENTS deeply using the NotebookLM MCP server and deliver a structured research brief. Optionally generate studio artifacts (slides, audio podcasts, videos, infographics, reports, mind maps) from the research.
Prerequisites
- NotebookLM MCP server must be configured. Install via:
nlm setup add claude-code - If NotebookLM MCP tools are not available, tell the user to run the setup command and restart their session.
Research Workflow
Step 1: Define Scope
Determine the research type based on the user's request:
| Type | Focus |
|---|---|
| Market Research | Industry trends, market sizing, opportunities, TAM/SAM/SOM |
| Competitive Intel | Competitor analysis, positioning gaps, feature comparisons |
| Client/Prospect Research | Company background, pain points, decision makers, recent news |
| Trend Analysis | Technology trends, adoption patterns, forecasts, emerging players |
| Proposal Research | Background for proposals, sector-specific data, case studies |
| Academic/Technical | Papers, frameworks, methodologies, state of the art |
Tell the user what you plan to research and confirm the angle:
"I'll research [topic]. My angle: [specific focus]. I'll investigate: [2-3 specific questions]. Sound right, or should I adjust?"
Wait for confirmation before proceeding.
Step 2: Create NotebookLM Notebook
Use notebook_create to create a notebook named: Research: [Topic] - [YYYY-MM-DD]
Step 3: Add Context Sources
Use source_add to seed the notebook with relevant context:
- Add any URLs the user provides (articles, company pages, reports)
- Add any documents or files the user references
- Add text summaries of relevant background if no URLs are available
- If researching a company, add their website, LinkedIn, recent press
Step 4: Run Research
Use research_start with a well-crafted query based on the topic and context.
Mode selection:
- Default:
"fast"(~60 seconds, ~10 sources) -- good for most queries - Use
"deep"only if the user explicitly asks for exhaustive research (can take 10+ minutes and may stall at 0 sources)
Tip: Run direct WebSearch calls in parallel with NotebookLM for faster initial data gathering while the research engine works.
Poll research_status until complete. Use the query parameter as fallback matching -- task IDs can change between research_start and research_status calls.
Step 5: Import Discovered Sources
Use research_import to bring discovered sources into the notebook for deeper analysis.
Step 6: Query for Insights
Use notebook_query to ask 3-5 targeted questions based on the research type:
1. Overview: "What are the key findings about [topic]?" 2. Opportunities: "What opportunities or gaps exist in this space?" 3. Actions: "What are the most actionable insights from this research?" 4. Risks: "What are the main risks, challenges, or counterarguments?" 5. Custom: A question specific to the research type (e.g., "Who are the top 5 competitors and how do they differentiate?" for competitive intel)
Step 7: Write Research Brief
Save the findings to a local file using the research brief template:
File path: research/[topic-slug]-[YYYY-MM-DD].md
Use the template from research-brief-template.md to structure the output. Create the research/ directory if it does not exist.
Step 8: Present Takeaways
After saving, present the user with:
- 3-5 headline findings (bullets, direct, no filler)
- 1-2 recommended actions connected to the user's stated goals
- Surprises or contrarian findings -- anything that challenges assumptions
- The file path where the full brief is saved
- The NotebookLM notebook URL so the user can explore sources directly
Step 9 (Optional): Generate Studio Artifacts
Ask the user: "Want me to generate any artifacts from this research? Options: slides, audio (podcast), video, infographic, report, mind map."
If yes, use studio_create with the notebook_id from Step 2.
Available artifact types and recommended settings:
| Type | Key params | Best for |
|---|---|---|
slide_deck | slide_format: detailed_deck or presenter_slides; slide_length: short or default | Executive presentations, client pitches |
audio | audio_format: deep_dive, brief, critique, or debate; audio_length: short, default, long | Podcast-style deep dives, learning on the go |
video | video_format: explainer, brief, cinematic; visual_style: auto_select, classic, whiteboard, etc. | Visual explainers, social media content |
infographic | orientation: landscape, portrait, square; infographic_style: professional, bento_grid, etc. | One-pagers, social sharing |
report | report_format: Briefing Doc, Study Guide, Blog Post, Create Your Own | Written deliverables, summaries |
mind_map | title | Visual knowledge mapping |
Common params for all artifact types:
language: Set to the user's preferred language (e.g.,"en","es","pt")focus_prompt: A clear directive about what to emphasize in the artifactconfirm: Must betrueto proceed with generation
After creating an artifact: 1. Poll studio_status until completed (audio/video: 5-15 min; slides/infographics: 2-5 min) 2. Use download_artifact to save locally if needed 3. Provide the notebook URL so the user can access artifacts directly
Tips:
audiowithdeep_diveformat produces the best podcast-style analysisslide_deckwithdetailed_deckformat works best for standalone reading;presenter_slidesis better when accompanied by speaker notes- Audio status may show
"unknown"once completed -- check foraudio_urlpresence instead of waiting for a"completed"status
Notes
- Fast mode is recommended as the default. Deep mode is powerful but can take 10+ minutes and occasionally stalls.
- Always confirm the research scope with the user before starting -- a well-scoped query produces dramatically better results.
- The research brief template ensures consistent, actionable output across all research types.
Additional Resources
- research-brief-template.md -- Template for structuring research brief output
Research Brief: [Topic]
Date: [YYYY-MM-DD] Type: [Market Research | Competitive Intel | Client Research | Trend Analysis | Proposal Research | Academic/Technical] NotebookLM Notebook: [notebook name and URL]
---
Executive Summary
[2-3 sentences: what was researched, why it matters, top-line finding]
---
Key Findings
1. [Finding Title]
[Detail with data points, statistics, or evidence where available]
2. [Finding Title]
[Detail with supporting evidence]
3. [Finding Title]
[Detail with supporting evidence]
---
Opportunities
- [Specific opportunity with context on why it matters]
- [Specific opportunity with potential impact]
---
Risks & Challenges
- [Risk or challenge with context and severity assessment]
- [Risk or challenge with mitigation considerations]
---
Recommended Actions
1. [Action] -- [Why this matters and suggested next step] 2. [Action] -- [Why this matters and suggested next step]
---
Sources
- [Source 1 -- title, URL, and relevance]
- [Source 2 -- title, URL, and relevance]
- [Source 3 -- title, URL, and relevance]
---
Generated via deep-research-notebooklm skill using NotebookLM MCP