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Claude-code-templates deep-research-notebooklm

Deep research skill powered by NotebookLM MCP. Conducts structured multi-source research (market analysis, competitive intel, trend analysis, prospect research) using Google NotebookLM as the research engine, then delivers formatted briefs and optional studio artifacts (slides, audio podcasts, videos, infographics, reports, mind maps).

install
source · Clone the upstream repo
git clone https://github.com/davila7/claude-code-templates
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/davila7/claude-code-templates "$T" && mkdir -p ~/.claude/skills && cp -r "$T/cli-tool/components/skills/ai-research/deep-research-notebooklm" ~/.claude/skills/davila7-claude-code-templates-deep-research-notebooklm && rm -rf "$T"
manifest: cli-tool/components/skills/ai-research/deep-research-notebooklm/SKILL.md
source content

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:

TypeFocus
Market ResearchIndustry trends, market sizing, opportunities, TAM/SAM/SOM
Competitive IntelCompetitor analysis, positioning gaps, feature comparisons
Client/Prospect ResearchCompany background, pain points, decision makers, recent news
Trend AnalysisTechnology trends, adoption patterns, forecasts, emerging players
Proposal ResearchBackground for proposals, sector-specific data, case studies
Academic/TechnicalPapers, 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:

TypeKey paramsBest 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 artifact
  • confirm
    : Must be 
    true
    to 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:

  • audio
    with 
    deep_dive
    format produces the best podcast-style analysis
  • slide_deck
    with 
    detailed_deck
    format works best for standalone reading; 
    presenter_slides
    is better when accompanied by speaker notes
  • Audio status may show 
    "unknown"
    once completed -- check for 
    audio_url
    presence 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