
Deep Research via NotebookLM
FreeConduct structured research and generate insights effortlessly.
Free · Opens the source repo
What Deep Research via NotebookLM does
The Deep Research via NotebookLM skill enables users to conduct comprehensive and structured research across various domains, leveraging the capabilities of the NotebookLM MCP server. This skill is particularly useful for professionals involved in market analysis, competitive intelligence, and academic research. By defining the research scope, users can focus on specific areas such as market trends, competitor analysis, or client insights, ensuring that the research is relevant and targeted.
The workflow begins with defining the research type and confirming the angle with the user. This ensures clarity and alignment on the objectives before proceeding. Once the scope is set, the skill utilizes the NotebookLM MCP to create a dedicated notebook for the research topic, where relevant context sources can be added. This includes URLs, documents, and summaries, providing a rich foundation for the research.
After gathering context, the skill initiates the research process using carefully crafted queries. Users can choose between a fast mode for quick insights or a deep mode for exhaustive research, depending on their needs. The findings are then imported into the notebook for analysis, where targeted queries can extract key insights, opportunities, and risks related to the research topic.
Finally, the skill compiles the findings into a structured research brief, saved in a specified format, and presents key takeaways to the user. Additionally, users have the option to generate various studio artifacts such as slides, audio podcasts, or infographics, making it a versatile tool for both research and presentation purposes.
When to use it
Use this skill when you need to conduct in-depth research on market trends, competitors, or specific clients and want structured outputs.
When not to use it
This skill may not be suitable for quick, informal research or when the NotebookLM MCP server is not configured properly.
What you can build with it
Market Trend Analysis
Conduct a thorough analysis of current market trends and opportunities using structured research.
Competitive Landscape Review
Analyze competitors and identify positioning gaps to inform strategic decisions.
Client Prospecting Research
Gather insights on potential clients, including background information and recent news, to tailor outreach.
How to install Deep Research via NotebookLM
View source1. Install with the skills CLI
npx skills add davila7/claude-code-templates/deep-research-notebooklm --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by davila7Deep 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:
- Overview: "What are the key findings about [topic]?"
- Opportunities: "What opportunities or gaps exist in this space?"
- Actions: "What are the most actionable insights from this research?"
- Risks: "What are the main risks, challenges, or counterarguments?"
- 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:
- Poll
studio_statusuntilcompleted(audio/video: 5-15 min; slides/infographics: 2-5 min) - Use
download_artifactto save locally if needed - 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
Frequently asked questions about Deep Research via NotebookLM
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