Deep research skill

Deep Research

Free Perplexity/Gemini-level deep research for any AI coding agent. Combines NotebookLM's Gemini-powered research engine with iterative web search, domain-aware routing, and post-research artifact generation.

Activation

Triggered by /deep-research "topic" or intent detection ("research this", "deep dive into", "investigate").

Argument Parsing

• "topic" — required, the research query
• --domain maritime|legal|academic — optional domain boost
• --continue — resume previous research session
• --compare "X vs Y" — structured comparison mode

If no arguments provided, ask: "What topic should I research?"

Dependency Check

Before starting, determine available capabilities:

1. Try notebooklm status first. If command not found, try python3 -m notebooklm status or python -m notebooklm status. Use whichever works for all subsequent notebooklm commands.

   • If success: Full mode (NotebookLM + WebSearch)
   • If all fail: Fallback mode (WebSearch only)

2. If fallback mode, inform user:

   "NotebookLM not detected. Running in web-search-only mode. For full features (deep research, podcast, video, slides, quiz), install: pip install notebooklm-py && notebooklm login"

3. Store mode for pipeline decisions.

Pre-flight

Present this prompt and WAIT for user response before proceeding:

Research Topic: "{topic}"

Depth:
  1 = Quick (fast mode, 5-10 sources, ~1 min)
  2 = Moderate (fast + 1 WebSearch round, 10-15 sources)
  3 = Standard (deep mode, 20+ sources, ~3 min)  [default]
  4 = Deep (deep + 1 WebSearch round, 30+ sources)
  5 = Exhaustive (deep + 2 WebSearch rounds, 40+ sources)

Source focus:
  A = Everything (web + your notebooks)  [default]
  B = Academic only (papers, journals, research)
  C = News & current events (last 12 months)
  D = Technical docs & specs
  E = Custom (tell me what to focus on)

Enter choices (e.g. "3, A") or press Enter for defaults:

Parse response:

• Default if empty: depth=3, focus=A
• Extract depth (1-5) and focus (A-E)
• If focus=E, ask follow-up: "What should I focus on?"

Pipeline — Full Mode (NotebookLM available)

Step 1: Check existing notebooks

Run: notebooklm list --json

Search results for notebooks with titles matching the topic. If found, ask user: "Found existing notebook '{title}' with {n} sources. Use it? (y/n)"

• If yes: notebooklm use {id}, skip to Step 3
• If no: continue to Step 2

Step 2: Create research notebook

Run: notebooklm create "Research: {topic}" --json Parse notebook ID from output. Run: notebooklm use {id}

Step 3: Query existing sources (if focus=A and existing notebook)

If existing notebook was selected, run: notebooklm ask "What information do you have about {topic}?" --json Store response as baseline context.

Step 4: Launch deep research

Determine mode from depth:

• Depth 1-2: --mode fast
• Depth 3-5: --mode deep

Run: notebooklm source add-research "{topic_query}" --mode {fast|deep} --no-wait

Show progress: [2/5] Starting deep research... (mode: {mode})

Step 5: Wait for research completion

Run: notebooklm research wait --import-all --timeout 300

Show progress: [3/5] Waiting for sources... (processing...)

When complete, run: notebooklm source list --json Report: [3/5] {n} sources imported and ready.

Step 6: Extra WebSearch rounds (depth > 3)

If depth >= 4, run 1 WebSearch round:

• Generate 3-5 targeted search queries based on initial findings
• For each query: WebSearch, then read top 3 results with WebFetch
• Add discovered URLs as sources: notebooklm source add "{url}"

If depth = 5, run a second WebSearch round:

• Generate 3-5 NEW queries based on combined findings
• Same process: search, fetch, add as sources
• Wait for new sources: notebooklm source wait {id}

Show progress: [4/5] Running additional searches... ({n} extra sources)

Step 7: Domain boost (if --domain specified)

Run domain-specific searches from the Domain Boost section below. Add discovered URLs as sources to the notebook.

Step 8: Synthesize

Run structured synthesis query:

notebooklm ask "Based on ALL sources in this notebook, provide a comprehensive research report on '{topic}'.

Structure your response as:

1. EXECUTIVE SUMMARY (3-5 sentences, key takeaways)

2. MAIN FINDINGS (organized by theme, each finding citing specific sources)

3. KEY FINDINGS (bullet list of most important discoveries)

4. CONTRADICTIONS & OPEN QUESTIONS (where sources disagree or gaps exist)

5. For each claim, note which source(s) support it.

Be thorough, analytical, and cite sources precisely." --json

Parse response and extract references. Format into the Report Format below.

Pipeline — Fallback Mode (WebSearch only)

Used when NotebookLM is not available. Iterative WebSearch + WebFetch.

Round 1: Broad search

Generate 5 search queries from the topic (different angles). For each query:

1. WebSearch to collect top 5 URLs
2. WebFetch top 3 URLs to extract key findings
3. Store findings + source URLs

Show progress: [1/{total_rounds}] Broad search... ({n} sources found)

Round 2+ (if depth > 1): Deep dive

For each round (up to depth-1 additional rounds):

1. Analyze findings from previous round
2. Identify gaps and unanswered questions
3. Generate 3-5 new targeted queries
4. WebSearch + WebFetch for each
5. Merge new findings with existing

Show progress: [{round}/{total_rounds}] Deep dive round {n}... ({total} sources)

Domain boost in fallback

Same domain-specific queries as full mode, but results stay in-memory instead of being added to a NotebookLM notebook.

Synthesis in fallback

Compile all findings into the Report Format below. Synthesis is done by the agent directly from collected findings.

Limitations in fallback mode

Post-research actions NOT available without NotebookLM:

• Podcast generation
• Video generation
• Slide deck generation
• Quiz/flashcard generation
• Follow-up questions against persistent notebook

Available actions in fallback:

• Save as .md
• Go deeper (additional WebSearch rounds)
• Compare mode

Domain Boost

When --domain is specified, add these targeted searches to the pipeline.

Maritime (--domain maritime)

Additional search queries:

• "{topic}" site:imo.org
• "{topic}" SOLAS regulation
• "{topic}" STCW code
• "{topic}" ISM Code
• "{topic}" site:iacs.org.uk
• "{topic}" Maritime Safety Committee MSC circular
• "{topic}" class society guidelines

Source priority (highest to lowest):

1. IMO resolutions, circulars, guidelines
2. SOLAS/STCW/ISM Code references
3. IACS unified requirements
4. Class society publications (Lloyd's, DNV, BV, ABS)
5. Maritime industry papers (BIMCO, ICS, INTERCARGO)
6. General maritime publications

Citation format: include regulation references when available. Example: "SOLAS Ch. III, Reg. 19.3.3" or "STCW Code Table A-VI/1"

Legal (--domain legal)

Additional search queries:

• "{topic}" legislation regulation
• "{topic}" official journal law
• "{topic}" court decision ruling
• "{topic}" regulatory framework directive
• "{topic}" compliance requirements

Source priority:

1. Official government legislation/gazettes
2. Court decisions and rulings
3. Regulatory body publications
4. Legal databases and commentary
5. Law firm analysis and white papers

Academic (--domain academic)

Additional search queries:

• "{topic}" research paper study
• "{topic}" peer-reviewed journal
• "{topic}" systematic review meta-analysis
• "{topic}" site:arxiv.org
• "{topic}" site:researchgate.net
• "{topic}" IEEE conference proceedings

Source priority:

1. Peer-reviewed journal articles
2. Systematic reviews and meta-analyses
3. Conference proceedings
4. Preprints (arXiv, SSRN)
5. University research reports
6. Technical reports and white papers

Report Format

Format the final output as a Gemini Deep Research-style report:

# {Topic} — Deep Research Report

**Generated:** {date} | **Sources:** {count} | **Depth:** {depth_label} | **Domain:** {domain or "General"}

## Executive Summary

{3-5 sentence overview of the most important findings. Lead with the answer,
not the process. What does the user need to know?}

## 1. {First Major Theme}

{Detailed analysis. Every factual claim includes a footnote reference.^1
When sources disagree, note the disagreement explicitly.^2,3}

## 2. {Second Major Theme}

{Continue with thematic sections. Number of sections scales with depth:
depth 1-2 = 2-3 sections, depth 3 = 3-5 sections, depth 4-5 = 5-8 sections.}

## Key Findings

- {Most important finding — with practical implication}
- {Second finding — actionable takeaway}
- {Third finding — what this means for the user}

## Contradictions & Open Questions

- {Where Source A says X but Source B says Y — explain why}
- {Gaps in current research or knowledge}
- {Areas where no consensus exists}

---

### Sources

^1 {Title} — {URL} — [{credibility_tag}]
^2 {Title} — {URL} — [{credibility_tag}]
^3 {Title} — {URL} — [{credibility_tag}]

Source Credibility Tags

Assign one tag to each source based on its origin:

Tag	Criteria
official	Government body, regulatory org, international org (IMO, EU, WHO)
academic	Peer-reviewed journal, university publication, .edu domain
industry	Professional association, established trade publication
news	Major news outlet, established journalist
blog	Personal site, forum, social media, unverified source

Display format in sources list: ^1 Title — URL — [official]

Post-Research Actions

After displaying the report, present this menu:

Research complete! What next?

  [S] Save as .md file
  [P] Generate podcast from findings
  [V] Generate video explainer
  [D] Generate slide deck
  [Q] Generate quiz/flashcards
  [F] Ask follow-up questions
  [+] Go deeper on a specific section
  [C] Compare with another topic
  [X] Done

Choose (or multiple, e.g. "S, P"):

In fallback mode, only show: S, F (as new search), +, C, X.

Action: Save as .md [S]

Ask: "Where should I save the report?" Wait for path. Default suggestion: ./research/{topic-slug}.md Write the report to the specified path.

Action: Podcast [P] (Full mode only)

notebooklm generate audio "Create an engaging podcast discussion about the research findings. Focus on the most important and surprising discoveries. Make it conversational and accessible." --json

Note the artifact ID. Inform user: "Podcast generating (~10-20 min). I'll download it when ready." Spawn background agent to wait + download: notebooklm artifact wait {id} && notebooklm download audio ./research/{topic-slug}-podcast.mp3

Action: Video [V] (Full mode only)

notebooklm generate video "Create an explainer video covering the key findings of this research." --json

Same pattern: note artifact ID, spawn background agent for wait + download to ./research/{topic-slug}-video.mp4

Action: Slide Deck [D] (Full mode only)

notebooklm generate slide-deck --format detailed --json

Download as .pptx when ready: notebooklm download slide-deck ./research/{topic-slug}-slides.pptx --format pptx

Action: Quiz/Flashcards [Q] (Full mode only)

Ask: "Quiz or flashcards?"

Quiz:

notebooklm generate quiz --difficulty medium --json

Download: notebooklm download quiz ./research/{topic-slug}-quiz.md --format markdown

Flashcards:

notebooklm generate flashcards --difficulty medium --json

Download: notebooklm download flashcards ./research/{topic-slug}-cards.md --format markdown

Action: Follow-up [F]

Ask: "What would you like to know more about?"

• Full mode: notebooklm ask "{follow-up question}" --json
• Fallback mode: Run new WebSearch round focused on the follow-up question

Display answer, then show the menu again.

Action: Go Deeper [+]

Ask: "Which section should I investigate further? (enter number)" Take the section topic, run an additional research round:

• Full mode: notebooklm source add-research "{section topic details}" --mode deep
• Fallback mode: Additional WebSearch round on that section

Re-synthesize the specific section with new sources. Display updated section. Show menu again.

Action: Compare [C]

Ask: "Compare '{topic}' with what?" Transition to compare mode with current topic as side A. Run full research pipeline on side B. Generate comparison report (see Compare Mode section).

Continue Mode (--continue)

When invoked with --continue:

1. Run notebooklm list --json
2. Filter notebooks with titles starting with "Research:"
3. Present list:

Previous research sessions:

  1. "Research: ballast water treatment" (24 sources)
  2. "Research: enclosed space regulations" (18 sources)
  3. "Research: AI in maritime training" (12 sources)

Pick a session to continue (or 0 for new research):

4. If user picks a session:

   • notebooklm use {id}
   • Ask: "What aspect should I research further?"
   • Run additional research round with the new query
   • Re-synthesize all sources (old + new)
   • Display updated report
   • Show post-research menu

5. If user picks 0: start normal research flow

In fallback mode, --continue is not available (no persistent notebooks). Inform user: "Continue mode requires NotebookLM. Install with: pip install notebooklm-py && notebooklm login"

Compare Mode (--compare "X vs Y")

When invoked with --compare:

1. Parse X and Y from arguments
2. Ask depth (same pre-flight prompt, default=3)
3. Create notebook: notebooklm create "Research: {X} vs {Y}" --json
4. Add research for X: notebooklm source add-research "{X}" --mode deep
5. Add research for Y: notebooklm source add-research "{Y}" --mode deep
6. Wait for both to complete
7. Synthesize with comparison prompt:

notebooklm ask "Compare {X} and {Y} based on all sources. Structure as:

1. OVERVIEW: What is X? What is Y? (2-3 sentences each)

2. COMPARISON TABLE: Side-by-side comparison of key dimensions
   | Dimension | X | Y |

3. STRENGTHS: What X does better, what Y does better

4. WEAKNESSES: Limitations of each

5. USE CASES: When to choose X, when to choose Y

6. VERDICT: Your recommendation with reasoning

Cite sources for all claims." --json

8. Format as comparison report with footnotes
9. Show post-research menu

In fallback mode, compare runs two separate WebSearch pipelines and synthesizes both.

Progress Indicator

Display real-time status throughout the pipeline. Update after each step:

[1/6] Checking existing notebooks...
[2/6] Creating research notebook...
[3/6] Running deep research... (mode: deep)
[4/6] Waiting for sources... (18 found, processing...)
[5/6] Running domain-specific searches... (+3 sources)
[6/6] Synthesizing findings...

Done — 24 sources analyzed. Report below.

Step count adjusts based on pipeline:

• No domain boost: 5 steps
• With domain boost: 6 steps
• With extra WebSearch rounds: +1 per round
• Fallback mode: [{round}/{total_rounds}] format

Error Handling

Error	Detection	Action
NotebookLM not authenticated	notebooklm status fails with auth error	Show: "Run notebooklm login to authenticate"
NotebookLM not installed	notebooklm command not found	Switch to fallback mode, inform user
Research timeout	research wait returns exit code 2	"Research timed out. Showing partial results from {n} sources found so far."
Rate limit on generation	generate returns exit code 1 with rate limit	"Rate limited. Try again in 5-10 minutes, or use NotebookLM web UI."
No sources found	Research returns 0 sources	"No sources found via NotebookLM. Falling back to web search." Then run fallback pipeline.
WebSearch returns no results	All queries return empty	"Could not find relevant sources. Try rephrasing your topic or using a broader query."
Source processing stuck	Sources stay in "processing" > 5 min	Proceed with ready sources, note incomplete ones