Deep research skill powered by NotebookLM MCP. Conducts structured multi-source research (market analysis, competitive intel, trend analysis, prospect research)
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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.
nlm setup add claude-codeDetermine 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.
Use notebook_create to create a notebook named:
Research: [Topic] - [YYYY-MM-DD]
Use source_add to seed the notebook with relevant context:
Use research_start with a well-crafted query based on the topic and context.
Mode selection:
"fast" (~60 seconds, ~10 sources) -- good for most queries"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.
Use research_import to bring discovered sources into the notebook for deeper analysis.
Use notebook_query to ask 3-5 targeted questions based on the research type:
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.
After saving, present the user with:
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 be true to proceed with generationAfter creating an artifact:
studio_status until completed (audio/video: 5-15 min; slides/infographics: 2-5 min)download_artifact to save locally if neededTips:
audio with deep_dive format produces the best podcast-style analysisslide_deck with detailed_deck format works best for standalone reading; presenter_slides is better when accompanied by speaker notes"unknown" once completed -- check for audio_url presence instead of waiting for a "completed" status