Notebooklm Create

notebooklm-create

End-to-end workflow for building a complete NotebookLM topic notebook: deep research, source loading, full Studio, curated prompts. Orchestrates the notebooklm-rpc MCP tools with domain-specific gotcha handling encoded.

Relationship to notebooklm-skill

• notebooklm-skill = low-level API reference (notebooklm-py CLI)
• This skill (`notebooklm-create`) = high-level workflow orchestration using the notebooklm-rpc MCP tools available in this session

If the user just wants to call a single API (e.g., "list my notebooks"), use notebooklm-skill or the MCP tool directly. If they want to BUILD a research notebook from a topic, use this skill.

Why this workflow exists

Building a rich NotebookLM notebook for a topic has repeatable shape but is strewn with gotchas that cost real time if rediscovered:

• Some domains silently refuse NotebookLM's URL fetcher (Medium, Quora)
• URL adds cascade-fail when issued in parallel — must be sequential
• llms.txt URLs need the trailing .md stripped before adding
• Studio artifacts split into synchronous (mind map, reports, flashcards, quiz, data table) and async (audio, video, infographic, slide deck) with different polling behavior
• The Studio API classifies quiz artifacts as type: flashcards once generated (title disambiguates)
• confirm=True is mandatory on every Studio creation tool AND requires explicit user approval

This skill encodes all of that so future runs don't relearn it.

Workflow — the 7 phases

Run these in order. Each phase has a clear hand-off to the next.

Phase 1 — Capture intent

Ask or infer:

1. What's the topic? (e.g., "cmux", "ArgoCD image updater", "Azure landing zones") 2. Any seed URLs the user already wants included (videos, blog posts, GitHub repos)? 3. Which forums to cover? Defaults: Reddit, Hacker News, GitHub Discussions. Optional: Discord (captured as text — not URL-indexable), Quora (usually empty for technical topics; confirm via research) 4. Target notebook title — default convention: {topic} :: docs (matches user's existing naming pattern visible via notebook_list) 5. Does the user want the full Studio (all 10 artifacts) or selective?

If the topic name is ambiguous (multiple projects share the name — common: cmux = manaflow-ai vs craigsc vs coder), anchor disambiguation on the user's seed URLs before researching.

Phase 2 — Deep research

Goal: produce two artifacts — a research synthesis and a community content dossier. Both become text sources in the notebook.

Read references/prompt-library.md for prompt starters. Use WebFetch on user-provided seed URLs first to lock in disambiguation, then WebSearch for canonical repo / docs / llms.txt.

Dispatch two parallel agents (via the Agent tool with general-purpose subagent):

1. Research synthesis agent — produces 2000–3000 word markdown covering overview, architecture, features, comparisons, installation, traction, limitations, official URLs. Output template: assets/research_synthesis_template.md.

2. Community content agent — searches Reddit, Hacker News, GitHub Discussions for threads, extracts verbatim quotes with attribution. Captures Discord community texture by pulling equivalent content from GitHub Discussions (Discord isn't publicly scrapeable). Confirms Quora status (usually no threads for technical topics). Output template: assets/community_content_template.md.

Both agents should return ready-to-paste markdown. Save locally under MEMORY/WORK/<slug>/.

Phase 3 — Create the notebook

Use mcp__notebooklm-rpc__notebook_create with the agreed title.

mcp__notebooklm-rpc__notebook_create(title="{topic} :: docs")

Capture the returned notebook.id — you'll need it for every subsequent call.

Verify no duplicate exists first via mcp__notebooklm-rpc__notebook_list (filter titles case-insensitively for the topic term).

Phase 4 — Load sources (SEQUENTIAL — critical)

Read references/url-gotchas.md for the domain blocklist and URL-cleaning rules before calling any add tool.

Order of source types to add (each as a separate, sequential call — never in parallel):

1. User's seed URLs (YouTube, blog posts, etc.) 2. Official repo / website / docs 3. Hacker News discussion(s) 4. Reddit thread URL(s) — keep the trailing / that Reddit prefers 5. GitHub Discussions / Issues URLs with relevant community content 6. Third-party reviews / comparative discussions 7. After all URL sources: add the research synthesis and community content as text sources via mcp__notebooklm-rpc__notebook_add_text

DO NOT attempt to add:

• medium.com/* — always fails
• quora.com/* — always fails (as of 2026-04-21; see url-gotchas.md)
• linkedin.com/* — typically fails (auth gates)

If a domain is uncertain, probe with WebFetch first — if that returns bot-detection content, assume NotebookLM will fail too and capture as text instead.

If adding an llms.txt URL, strip any trailing .md before the call (e.g., foo.com/llms.txt, not foo.com/llms.txt.md).

Sequential sample pattern:

# For each url in ordered_list:
mcp__notebooklm-rpc__notebook_add_url(notebook_id=NB, url=url)
# wait for success, then next

Phase 5 — Generate full Studio (requires user approval)

Every Studio tool takes confirm=True. The MCP server explicitly states user approval is required before setting it. Present the plan to the user, get approval, then dispatch.

Read references/studio-quirks.md for sync vs async classification and known API quirks.

Recommended order (async-first minimizes total wall-clock):

1. audio_overview_create — async, ~60s+ 2. video_overview_create — async, several minutes 3. infographic_create — async, several minutes 4. slide_deck_create — async, several minutes 5. mind_map_create — synchronous 6. report_create(format="Briefing Doc") — synchronous 7. report_create(format="Study Guide") — synchronous 8. flashcards_create — synchronous 9. quiz_create(question_count=10) — synchronous (note: classified as type: flashcards in studio_status) 10. data_table_create(description=...) — synchronous

For each async artifact, pass a focus_prompt tailored to the topic — see references/mcp-tool-map.md for recommended focus prompts per tool.

After dispatching, poll once via mcp__notebooklm-rpc__studio_status after ~45s, then again after 2–3 minutes. Async media can take 5–10 minutes to render.

Phase 6 — Curate chat prompts

Add a text source containing 9 NotebookLM chat prompts adapted to the topic. Base templates live in references/prompt-library.md — they come from two public articles (XDA Developers, AI Fire) and are pre-mapped to structural goals:

1. Five Essential Questions (study) 2. Find the Interesting Bits (insight mining) 3. Quiz Show (gamified review) 4. Content Analyst Report (repurposing) 5. Community → Action Plan (roadmap synthesis) 6. SEO Outline (competitive content) 7. 360° Feedback on Marketing (voice-of-multi-persona critique) 8. Study Guide Kit (onboarding curriculum) 9. Conference Talk Script (narrative pitch)

Replace the topic-specific placeholders in each template with concrete references from the research (actors, quotes, key architectural facts). Save to both:

• A local markdown file under MEMORY/WORK/<slug>/prompts.md for reuse
• A text source inside the notebook via mcp__notebooklm-rpc__notebook_add_text titled "9 Curated NotebookLM Prompts for {topic}"

Phase 7 — Verify

mcp__notebooklm-rpc__notebook_get(notebook_id=NB)
mcp__notebooklm-rpc__studio_status(notebook_id=NB)

Confirm:

• Notebook title matches {topic} :: docs
• Source count matches expected (seed URLs + forum URLs + 2 text research sources + 1 prompts text source)
• Studio artifacts completed or still rendering (video/infographic/slide deck commonly still rendering at verification time — that's fine)
• No duplicate notebook was created

Report back to the user with:

• Notebook URL (notebooklm.google.com/notebook/{id})
• Table of studio artifacts with status
• Pointer to the 9 curated prompts

Tools & resources included

• scripts/add_urls_sequential.py — wraps the sequential-add pattern with the domain blocklist built in
• scripts/build_full_studio.py — dispatches all 10 Studio artifacts in the correct async-first order (prints the MCP call plan; actual MCP invocation happens from Claude's tool layer)
• scripts/adapt_prompts.py — takes a topic facts dict and emits the 9 prompts with placeholders filled
• references/url-gotchas.md — domain blocklist + URL-cleaning rules
• references/studio-quirks.md — sync vs async, quiz classification, confirm guard
• references/prompt-library.md — 9 base prompts with source attribution (XDA + AI Fire)
• references/mcp-tool-map.md — which MCP tool per phase + recommended focus prompts
• assets/research_synthesis_template.md — 9-section research doc scaffold
• assets/community_content_template.md — forum/community dossier scaffold
• assets/workflow_checklist.md — phase-by-phase checklist to copy into a work PRD
• samples/cmux_docs_walkthrough.md — worked example from the original session

When NOT to use this skill

• User wants to modify or dedupe an existing notebook — use notebooklm-skill or direct MCP calls
• User just wants to LIST notebooks or describe one — use the MCP tools directly
• User wants to add a single source to an existing notebook — direct MCP call is fine, no orchestration needed
• The task has no "build a research notebook" shape (e.g., "convert this PDF to audio") — use notebooklm-skill

References to read during execution

Anti-patterns (learned from real runs)

• Parallel URL adds → cascade fail. Always sequential.
• Adding Medium or Quora URLs → silently fail. Scrape content, add as text.
• Treating Studio like a single batch → confirm guard will block. Each tool needs its own confirm=True.
• Polling `studio_status` immediately → async artifacts show in_progress; wait 45s minimum.
• Checking `type` field to distinguish quiz from flashcards → both classify as flashcards post-generation. Use the artifact title.
• Forgetting to save the `notebook_id` → costs a redundant notebook_list call to recover it.

---

Gotchas

• Web research phase truncates at ~50 URLs — large topics need batching and manual aggregation; the truncation is silent.
• Sequential source upload preserves order; parallel upload doesn't — workflows that use & and wait in bash get random ordering and unstable citations.
• Source quotas reset at midnight Pacific — a script that hits the daily limit at 23:55 PT silently waits 5 minutes; one running at noon waits 12 hours.
• Full-studio generation: audio/video/slides/quiz/flashcards/etc. run in parallel after upload — if upload fails midway, the partial set still generates without error; verify all sources before generating.
• Notebook ID vs notebook title: the title is mutable; the ID isn't. Scripts that look up by title break on rename.

{TOPIC} Community Discussion: Reddit, Hacker News, GitHub, Discord, Quora

Subject: brief one-paragraph identity of {TOPIC}, including any name collisions to disambiguate.

Traction: one paragraph of quantitative signal — stars, forks, issue count, HN points, notable endorsements.

---

SOURCE 1: Hacker News — [Submission title]

URL: https://news.ycombinator.com/item?id=... Submitted: [date] by [user] | [X] points | [Y] comments

Author pitch (verbatim): "..."

Notable community comments:

• @user1: "verbatim quote"
• @user2: "verbatim quote"
• @user3 (critical): "verbatim quote"

Sentiment: [POSITIVE / MIXED / NEGATIVE] — [one-line rationale]

---

SOURCE 2: Reddit r/[subreddit] — [Thread title]

URL: https://reddit.com/r/[subreddit]/comments/...

• @user: "verbatim quote"
• @user (critical): "verbatim quote"

Sentiment: [...]

---

SOURCE 3: GitHub Discussion #[N] — [Title]

URL: https://github.com/org/repo/discussions/N

OP: "verbatim quote" Key reply (@user): "verbatim quote"

Sentiment: [...]

---

SOURCE N: X / Twitter

Notable posts with attribution.

---

SOURCE N+1: YouTube

Relevant videos with URLs.

---

SOURCE N+2: Discord

Discord content isn't publicly scrapeable by NotebookLM and should be captured here as text. If the Discord server is accessible to you, paste excerpts with [Discord: channel] attribution. Otherwise, note the invite URL and substitute equivalent content from GitHub Discussions.

Discord invite: [url if public]

---

SOURCE N+3: Quora

Status: [Usually: no threads found specifically discuss {TOPIC} — most technical audiences do not use Quora. Document the absence.]

If any threads exist, list URLs and verbatim question/answer excerpts.

---

OVERALL COMMUNITY SENTIMENT SUMMARY

Positive themes: 1. 2. 3.

Mixed/critical themes: 1. 2. 3.

Sentiment ratio across all sources: ~X% positive, ~Y% constructively critical, ~Z% hard negative.

{TOPIC}: Deep Research Synthesis

1. Overview

What {TOPIC} is, who built it, when it launched, positioning. Include the verbatim tagline from the official site and README. Capture the origin story in the creators' own words if quotable.

2. Architecture

• Core runtime/platform
• Key technical dependencies
• Rendering / execution model
• Configuration surface (what files it reads, how it extends)
• Persistence model (what survives restart)

3. Key Features

List and explain distinguishing features — each with at least one concrete example from the sources.

4. Integrations / Ecosystem

• Adjacent tools it works with
• Plugins, extensions, MCPs, skills built on it
• Import/export capabilities

5. Comparison

{TOPIC} vs alternatives. Use a table where possible. Explicitly call out which layer {TOPIC} operates at (e.g., substrate vs orchestrator vs review tool).

6. Installation & Usage

• Install steps (verbatim commands)
• Core commands and basic workflows
• Default shortcuts / keybindings

7. Traction & Reception

• GitHub stars over time
• HN / Reddit / social signal
• Notable endorsements (verbatim quotes with attribution)
• Geographic / community reach
• License

8. Limitations

Explicit, known trade-offs. Prefer maintainer statements over speculation.

9. Official URLs

Exhaustive list — every canonical URL you find:

Code & repo: -

Websites & docs: -

Creators & company: -

Community: -

Press / third-party: -

llms.txt: (if it exists — strip any trailing .md before adding to NotebookLM)

notebooklm-create — Workflow Checklist

Copy this checklist into a PRD.md under MEMORY/WORK/<slug>/ at the start of a run. Tick items as you complete them.

Phase 1 — Capture intent

• [ ] Topic name confirmed: _______________
• [ ] Seed URLs collected (user-provided):
• [ ] URL 1: _______________
• [ ] URL 2: _______________
• [ ] Forum coverage scope: Reddit ☐ HN ☐ GitHub Discussions ☐ Discord ☐ Quora ☐
• [ ] Notebook title decided: ____ :: docs
• [ ] Studio scope: full (all 10) ☐ selective ☐ (list: ____)
• [ ] Ambiguity check: multiple projects share this name? ☐ yes ☐ no
• If yes, disambiguation strategy: ____

Phase 2 — Deep research

• [ ] Seed URLs fetched (WebFetch) to anchor disambiguation
• [ ] Canonical repo URL identified
• [ ] Official docs / website URL identified
• [ ] llms.txt URL located (or confirmed absent)
• [ ] Research synthesis agent dispatched → artifact saved
• [ ] Community content agent dispatched → artifact saved

Phase 3 — Create notebook

• [ ] notebook_list run — no duplicate title exists
• [ ] notebook_create(title="____ :: docs") called
• [ ] Notebook ID captured: _______________

Phase 4 — Load sources (sequential)

• [ ] references/url-gotchas.md consulted
• [ ] URLs filtered: no Medium, no Quora, no LinkedIn
• [ ] Any llms.txt URLs have .md stripped
• [ ] Sequential URL adds executed — one at a time
• [ ] Research synthesis added as text source
• [ ] Community content added as text source

Phase 5 — Studio (requires user approval)

• [ ] User approval obtained for full studio dispatch
• [ ] references/studio-quirks.md consulted
• [ ] Async media dispatched first:
• [ ] audio_overview_create
• [ ] video_overview_create
• [ ] infographic_create
• [ ] slide_deck_create
• [ ] Synchronous dispatched second:
• [ ] mind_map_create
• [ ] report_create (Briefing Doc)
• [ ] report_create (Study Guide)
• [ ] flashcards_create
• [ ] quiz_create
• [ ] data_table_create
• [ ] studio_status polled after 45s
• [ ] studio_status polled again after 2–3 min

Phase 6 — Curate prompts

• [ ] 9 base prompts adapted to topic (via scripts/adapt_prompts.py)
• [ ] Prompts saved to MEMORY/WORK/<slug>/prompts.md
• [ ] Prompts added to notebook via notebook_add_text

Phase 7 — Verify

• [ ] notebook_get(notebook_id=NB) called
• [ ] Source count matches expected
• [ ] No duplicate placeholder sources from failed URL adds
• [ ] Studio artifacts: N completed, M in_progress
• [ ] Reported notebook URL to user
• [ ] Reported studio artifact status to user
• [ ] Memory entries updated if new gotchas discovered

MCP Tool Map — notebooklm-rpc

Which MCP tool to call at each workflow phase. All tools live under the mcp__notebooklm-rpc__ prefix.

Phase 1 — Capture intent

_No MCP calls. Conversation only._

Phase 2 — Deep research

_No notebooklm-rpc calls. Use WebFetch, WebSearch, and Agent (subagents) for research._

Phase 3 — Create notebook

Capture notebook.id from the notebook_create response.

Phase 4 — Load sources (sequential)

Order sensitivity: one-at-a-time. Wait for success response before next call.

Phase 5 — Studio generation

All require confirm: true AND user approval.

Async media (dispatch FIRST — longer render time)

Synchronous / fast-async (dispatch SECOND)

Polling & management

Phase 6 — Curate prompts

Phase 7 — Verify

Auth refresh

If any tool returns an auth error: do not save_auth_tokens manually. Run notebooklm-mcp-auth in the terminal (Bash tool) — it handles auth end-to-end.

Quick reference — full pipeline call order

1. notebook_list  # dedup check
2. notebook_create → capture notebook_id
3. notebook_add_url × N  (SEQUENTIAL, skip Medium/Quora)
4. notebook_add_text × 2  (research synthesis + community content)
5. audio_overview_create(confirm=true, focus_prompt=...)
6. video_overview_create(confirm=true, focus_prompt=...)
7. infographic_create(confirm=true, focus_prompt=...)
8. slide_deck_create(confirm=true, focus_prompt=...)
9. mind_map_create(confirm=true)
10. report_create(report_format="Briefing Doc", confirm=true)
11. report_create(report_format="Study Guide", confirm=true)
12. flashcards_create(confirm=true)
13. quiz_create(question_count=10, confirm=true)
14. data_table_create(description=..., confirm=true)
15. notebook_add_text (curated prompts)
16. studio_status  # poll 45s later
17. notebook_get   # final verify

Prompt Library — 9 curated NotebookLM chat prompts

Base templates for the 9 prompts this skill adds to every topic notebook. Three from XDA Developers, six from AI Fire. Adapted to be topic-agnostic — replace {TOPIC}, {CENTRAL_THEME}, {KEY_FACTS}, {KEY_ACTORS}, etc. with the topic-specific facts from Phase 2 research.

Attribution (preserve when adapting):

• Prompts 1–3: Alex Blake, XDA Developers, "3 prompts I use to get the most out of NotebookLM" — https://www.xda-developers.com/prompts-i-use-to-get-most-out-of-noteboooklm/
• Prompts 4–9: AI Fire, "6 NotebookLM Prompts That Do Your Hard Work For You" — https://www.aifire.co/p/6-notebooklm-prompts-that-do-your-hard-work-for-you

---

Prompt 1 — Five Essential Questions (XDA #1)

1.) Analyze all sources in this notebook about {TOPIC} and generate 5 essential questions that, when answered, capture the main points and core meaning of the material.
2.) When formulating your questions:
   a. Address the central theme — {CENTRAL_THEME}
   b. Identify key supporting ideas ({KEY_CONCEPTS})
   c. Highlight important facts or evidence ({KEY_FACTS})
   d. Reveal the creators' purpose or perspective ({ORIGIN_STORY})
   e. Explore significant implications — {IMPLICATIONS}
3.) Answer all 5 questions one-by-one in detail, citing specific sources.

Prompt 2 — Find the Interesting Bits (XDA #2)

What are the most surprising or interesting pieces of information or narratives in these sources about {TOPIC}? Focus on:
- Counter-intuitive design decisions
- Verbatim quotes from the creators, notable endorsers, or commenters
- Unexpected community dynamics
- Technical choices that differ from conventional wisdom
- Quotable lines that capture {TOPIC}'s identity

Include at least 8 key quotes with attribution.

Prompt 3 — Quiz Show (XDA #3)

You're hosting a fun quiz show with two hosts. The first host quizzes the second on concepts from this notebook about {TOPIC}. Include a mix of multiple choice and true/false questions covering: {KEY_CONCEPTS_LIST}.

Occasionally, the second host should get an answer wrong, and the first host should step in to explain the correct answer clearly, quoting sources. At the end, share the final score and a brief summary of how the second host did.

Prompt 4 — Content Analyst Report (AI Fire #1)

Act as a content strategy expert. Based on the sources in this notebook about {TOPIC}, create a full analysis with:

**1. Quick Summary:** 3 bullet points summarizing the most important ideas.

**2. Deep Analysis:**
   - Target Audience: Who is {TOPIC} for? Be specific.
   - Main Arguments: List the 3 main arguments {TOPIC} makes.
   - Best Quotes: 3 powerful sentences or facts from the sources, with attribution.

**3. Creative Ideas:**
   - Alternative Taglines: 2 other taglines (one curiosity-driven, one benefit-driven).
   - Social Media: A short LinkedIn post and a tweet/X post, with hashtags.

Prompt 5 — Community → Action Plan (AI Fire #2)

Act as a professional project secretary. Based on the community discussion sources in this notebook (forums, issues, threads), treat the collective conversation as a product meeting. Create a markdown summary with:

**1. Goal of the Meeting:** One sentence — what is the community collectively asking {TOPIC} to solve next?

**2. Main Voices:** Key speakers with handles/attribution.

**3. Summary of Main Discussions:** Main topics across threads.

**4. Important Decisions Made:** Concrete commitments maintainers announced.

**5. To-Do List:** Table with Task | Likely Owner | Priority for community-requested improvements.

**6. Unresolved Issues:** Open questions.

Prompt 6 — SEO Outline (AI Fire #3)

Act as an SEO expert and content editor. Based on ALL sources in this notebook about {TOPIC}:

**Part A: Competitor & Landscape Analysis**
1. Search Intent: When people search {EXPECTED_QUERIES}, what do they actually want?
2. Common Topics: 5 sub-topics every existing article/thread covers.
3. Content Gaps: Important sub-topics that are under-covered.

**Part B: Outline for a New Article**
1. 3 H1 suggestions (curiosity, benefit, authority).
2. Full H2/H3 structure including a gap-filling section from Part A.
3. Writer notes under each heading with specific facts/quotes/data from the notebook.

Prompt 7 — 360° Feedback on Marketing (AI Fire #4)

Create a "360-Degree Feedback Report" for the {TOPIC} README/homepage/marketing content captured in this notebook. Include:

**Section 1: Strict Editor's View**
   - 3 longest or weakest sentences with shorter rewrites.
   - Weakest claim — what needs more proof?

**Section 2: New Reader's View**
   - Confusing terms/concepts for someone new to the domain.
   - Most boring section. Why?

**Section 3: Marketing Expert's View**
   - Is the opening hook strong enough? If not, rewrite.
   - Stronger call-to-action for the end.

Prompt 8 — Study Guide Kit (AI Fire #5)

Act as a dedicated tutor for someone onboarding to {TOPIC}. Based on all sources, create a "Complete Study Guide Kit":

**1. Summary of Key Concepts:**
   The 5 most important ideas in {TOPIC}, each explained simply with a specific example from the sources.

**2. Terminology Flashcards:**
   12 important terms with short definitions. Format: "Term: Definition."

**3. Practice Questions:**
   - 5 essay-style questions covering architecture, philosophy, comparison, limitations, extensibility.
   - 10-question multiple-choice quiz (A, B, C, D).

**4. Answer Key:** Answers for the 10 MCQs with one-sentence rationale each, citing sources.

Prompt 9 — Conference Talk Script (AI Fire #6, adapted)

Act as a developer/product-advocate coach. I'm preparing a 15-minute conference talk about {TOPIC}, positioned as a maintainer or power user. Based on all sources, create a "Talk Prep Plan":

**Part 1: Audience Fit Analysis**
   3 biggest matches between {TOPIC}'s design choices and real pains evidenced in the community sources.

**Part 2: Talk Script**
   - 3–4 sentence opening hook naming the specific pain and pivoting to the {TOPIC} answer.
   - 3 "story moments" from the sources in STAR format (Situation, Task, Action, Result).

**Part 3: Audience Q&A Prep**
   3 smart questions the audience will likely ask, with grounded answers using direct source quotes.

---

Adaptation checklist

When adapting for a specific topic, replace:

• {TOPIC} — the project/subject name
• {CENTRAL_THEME} — one-line identity statement
• {KEY_CONCEPTS} — 4–6 technical sub-concepts
• {KEY_FACTS} — 3–5 verifiable data points (version, launch date, stars, funding)
• {ORIGIN_STORY} — who built it and why (one sentence)
• {IMPLICATIONS} — what layering/positioning matters
• {KEY_CONCEPTS_LIST} — comma-separated list for Quiz Show
• {EXPECTED_QUERIES} — 2–3 likely search queries

Replace every placeholder. Generic prompts produce generic outputs.

Studio Quirks — NotebookLM artifact generation

Quirks observed when calling the notebooklm-rpc Studio tools. Consult before Phase 5.

The confirm guard

Every Studio creation tool takes confirm: bool (default false). Calling with confirm=false returns an error.

Per the notebooklm-rpc MCP server instructions: Tools with confirm param require user approval before setting confirm=True.

Workflow: 1. Present the studio plan to the user (list of artifacts, options, focus prompts) 2. Get explicit approval (or treat a clear user request like "build the full studio" as scoped approval) 3. Then dispatch each tool with confirm=true

Do NOT hide this guard from the user. If in doubt, ask.

Sync vs async

Implication: Dispatch the longest async ones FIRST so they render in parallel with the shorter ones.

Quiz classified as flashcards

When you call quiz_create, the synchronous response correctly reports type: "quiz". But after generation completes, studio_status shows the quiz artifact with type: "flashcards" and a flashcard_count field.

Do not rely on the `type` field to distinguish quiz from flashcards post-generation. Use the artifact title (e.g., "Quiz cmux") or the original artifact_id you captured at creation.

Counts are approximations

Requested question_count: 10 → NotebookLM commonly returns 9. Flashcards behave similarly. Budget ±1–2 from the requested count.

Focus prompts

audio_overview_create, video_overview_create, infographic_create, slide_deck_create, and the "Create Your Own" report format accept a focus_prompt parameter. Use it. A targeted focus prompt dramatically improves grounding vs the default "summarize everything" behavior.

Good focus prompts:

• Name the topic explicitly
• List 3–5 specific sub-themes to emphasize
• Mention key actors, quotes, or facts from the sources
• Indicate the audience (e.g., "for developers evaluating X")

Bad focus prompts:

• Generic ("make it good")
• Longer than ~3 sentences (NotebookLM truncates)
• Instructions about structure the tool already knows (e.g., telling an audio overview to "have two hosts")

Polling

After dispatch, call mcp__notebooklm-rpc__studio_status(notebook_id=NB) after ~45s. Most synchronous artifacts will be complete. Async media (audio/video/infographic/slide deck) may still show in_progress — poll again after 2–3 minutes, or tell the user they'll finish rendering in the NotebookLM UI.

Audio overview formats

• deep_dive — two-host podcast, default, most engaging
• brief — shorter summary format
• critique — adversarial / analytical framing
• debate — two opposing positions

deep_dive is the right default. Pick brief only if the user explicitly wants ≤5 min.

Video overview visual styles

Accepted values: auto_select | classic | whiteboard | kawaii | anime | watercolor | retro_print | heritage | paper_craft.

Default to auto_select; NotebookLM picks based on content. Override only if the user specifies a style.

Report formats

• "Briefing Doc" — executive summary style
• "Study Guide" — student-facing, with study questions
• "Blog Post" — narrative, shareable
• "Create Your Own" — requires custom_prompt

For a typical topic notebook, generating both Briefing Doc and Study Guide covers the two dominant consumption modes (skim vs learn).

Recovery

If an artifact fails or produces poor output, delete and regenerate:

mcp__notebooklm-rpc__studio_delete(notebook_id=NB, artifact_id=AID)
# then re-call the create tool

URL Gotchas — NotebookLM source adds

Rules learned from real notebook builds. Consult before calling mcp__notebooklm-rpc__notebook_add_url.

Domain blocklist (known-failing)

NotebookLM's URL fetcher silently fails — or registers a broken placeholder source — on these domains. Scrape content with WebFetch/WebSearch, then add as text via `notebook_add_text` instead.

If a Quora or Medium URL add fails, NotebookLM may still create a broken placeholder source in the notebook — visible as the raw URL string with no title. Remove these via source_delete if they appear.

Sequential-only rule

notebook_add_url cascade-fails when called in parallel. The second call while the first is pending will frequently error or produce an incomplete source.

Always add URLs sequentially — wait for each call's success response before issuing the next. Parallel-tool-call is the wrong pattern here.

Same rule applies to notebook_add_text if you're adding many text sources back-to-back, though text adds are more tolerant.

URL cleaning

llms.txt

Strip any trailing .md from llms.txt URLs before adding:

• ✅ https://example.com/llms.txt
• ❌ https://example.com/llms.txt.md

NotebookLM fetches the URL literally; .md suffix produces a 404 or wrong content type.

Reddit

Reddit is tolerant of both forms, but prefer the old.reddit.com redirect target or the canonical reddit.com form with the trailing slug. Example:

• ✅ https://reddit.com/r/ClaudeCode/comments/1r9g45u/i_made_a_ghosttybased_terminal_with_vertical_tabs/
• ❌ https://www.reddit.com/r/ClaudeCode/comments/1r9g45u/ (works but loses the slug — title may be less informative)

GitHub

Direct links to /blob/main/README.md work. Prefer the root repo URL (e.g., github.com/org/repo) for the best auto-title; NotebookLM fetches the README automatically.

GitHub Discussions (/discussions/NNN) and Issues (/issues/NNN) load fine as URLs.

Hacker News

news.ycombinator.com/item?id=NNNNN works reliably. Include the top-level discussion, not individual comment permalinks.

YouTube

Full watch URLs work: youtube.com/watch?v=ID or youtu.be/ID. Short URLs are fine.

When in doubt, probe first

If the domain isn't on this list but you're unsure:

1. Run WebFetch on the URL with a trivial prompt 2. If WebFetch returns bot-detection content, auth-wall language, or empty body → NotebookLM will likely fail too. Scrape content and add as text. 3. If WebFetch returns real content → notebook_add_url usually succeeds.

Recovery if a bad URL was added

mcp__notebooklm-rpc__source_delete(notebook_id=NB, source_id=<bad_source_id>)

Source IDs are in the error-response metadata or visible via notebook_get.

Sample: cmux :: docs End-to-End Walkthrough

Real worked example of this skill applied to the topic cmux (manaflow-ai) — the native macOS terminal for parallel AI coding agents. Built on 2026-04-21. All IDs and URLs are verifiable.

Inputs from the user

"create a entirely cmux :: docs notebooklm, go to the web and make a deepresearch about that and add as source for this notebooklm

- https://www.youtube.com/watch?v=8oLP8oxqtOE

- https://vibecoding.app/blog/cmux-review

go to forum like reddit, discord, quora"

Phase 1 — Intent

• Topic: cmux — ambiguous (multiple projects share the name); anchor on user URLs
• Seed URLs: YouTube video + vibecoding blog
• Forums: Reddit, Discord, Quora explicitly named
• Title: cmux :: docs (matches existing {topic} :: docs convention)
• Studio: deferred to a second user turn ("entirely studio")
• Disambiguation: WebFetch on the two seed URLs confirmed manaflow-ai/cmux, not craigsc/cmux or coder/cmux

Phase 2 — Deep Research

Two parallel subagents dispatched:

Synthesis agent produced research_synthesis.md (12.8 KB, 9 sections per template). Key findings:

• cmux = native Swift/AppKit macOS terminal, built on libghostty
• Founders: Austin Wang + Lawrence Chen (Manaflow, YC S24)
• Launched Feb 19, 2026 — hit #2 on HN
• ~15k stars by April 2026
• Mitchell Hashimoto (Ghostty creator) publicly endorsed it
• Positioning: "primitive, not a solution"
• Layering: board → orchestrator → review → terminal (cmux) → agent

Community agent produced community_content.md (14.9 KB). Key findings:

• Hacker News Show HN (id=47079718) — 198 points, 77 comments, strongly positive
• 3 active Reddit threads (r/ClaudeCode, r/tmux, r/SaasDevelopers)
• GitHub Discussion #681 (session persistence gap) — most cited critical feedback
• Quora: no cmux threads exist — confirmed absent
• Discord server exists (discord.gg/xsgFEVrWCZ) — content captured indirectly from GitHub Discussions

Phase 3 — Create notebook

mcp__notebooklm-rpc__notebook_create(title="cmux :: docs")
→ notebook_id = e0ed6d5f-abdc-4957-9ccd-fd988f88970f

Pre-flight notebook_list confirmed no existing cmux-named notebooks.

Phase 4 — Sources (sequential)

11 URL sources added one at a time:

1. youtube.com/watch?v=8oLP8oxqtOE ✅ 2. vibecoding.app/blog/cmux-review ✅ 3. github.com/manaflow-ai/cmux ✅ 4. www.cmux.dev/ ✅ 5. cmux.com/docs/getting-started ✅ 6. news.ycombinator.com/item?id=47079718 ✅ 7. reddit.com/r/ClaudeCode/comments/1r9g45u/... ✅ 8. reddit.com/r/tmux/comments/1s2rnln/... ✅ 9. reddit.com/r/SaasDevelopers/comments/1sfecai/... ✅ 10. github.com/ComposioHQ/agent-orchestrator/discussions/526 ✅ 11. github.com/manaflow-ai/cmux/discussions/681 ✅

Failed adds (expected, per url-gotchas.md):

• quora.com/topic/Terminal-Emulators ❌ — NotebookLM returned Failed to add URL source
• quora.com/What-are-some-of-the-best-free-AI-agents-9 ❌ — same

Recovery: Captured Quora absence in the community content text source instead. Added a new feedback memory (feedback_quora_urls_fail.md) after observing the failure.

2 text sources added:

• cmux: Deep Research Synthesis (source id 4074bf68)
• cmux Community (Reddit, HN, GitHub, Discord, Quora) (source id 57e0fc1e)

Final count: 13 usable sources.

Phase 5 — Studio (second user turn)

User explicitly requested "entirely studio" — treated as scoped approval.

Dispatched in async-first order, all with confirm=true:

studio_status polled at 45s (6 completed) and again at 2 min (7 completed). Video/infographic/slide deck left rendering — reported to user with expected completion time.

Phase 6 — Curate prompts

adapt_prompts.py with the following facts:

{
  "topic": "cmux",
  "central_theme": "native macOS terminal for AI coding agents built on libghostty",
  "key_concepts": "libghostty rendering, OSC notification protocols, claude-teams, Ghostty config reuse",
  "key_facts": "YC S24 backed, launched Feb 19 2026, ~15k stars, #2 on Hacker News",
  "origin_story": "Austin Wang and Lawrence Chen built it after frustration with generic 'Claude is waiting for your input' notifications",
  "implications": "cmux is a terminal substrate, not an orchestrator",
  "key_concepts_list": "libghostty, OSC 9/99/777, claude-teams, Ghostty config, vertical tabs, notification rings, remote workspaces, AGPL",
  "expected_queries": "cmux, terminal for Claude Code, parallel AI agents macOS"
}

Emitted prompts.md, saved locally, then added to notebook as text source 4dfd83a6 titled "9 Curated NotebookLM Prompts for cmux".

Phase 7 — Verify

notebook_get(notebook_id=e0ed6d5f-...) returned:

• Title: cmux :: docs ✅
• 14 sources total (11 URL + 3 text: research, community, prompts)
• 2 Quora placeholder errors (noted, left in place — harmless)

Final reported to user:

• Notebook URL: https://notebooklm.google.com/notebook/e0ed6d5f-abdc-4957-9ccd-fd988f88970f
• 7/10 studio artifacts completed at verification time
• 9 curated prompts available as text source for chat use

Lessons captured as memory

New memory entries added during this run:

• feedback_quora_urls_fail.md — Quora URLs silently fail like Medium
• feedback_notebooklm_studio_quirks.md — quiz classification quirk, sync vs async polling
• project_cmux_notebook.md — notebook pointer with ID and metadata

These memories now prevent rediscovery in future runs of this skill.