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577206/knowledge-forge/notebooklm-obsidian-second-brain
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PublishedOctober 25, 2026 at 05:37 AM
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version: "1.0.0" name: notebooklm-obsidian-second-brain description: Use notebooklm-py, NotebookLM, Obsidian, and an agent workflow to turn source documents into a reviewed second-brain knowledge vault. Applies when users ask to automate NotebookLM, generate study/research artifacts, or write NotebookLM outputs into Obsidian/Markdown.


NotebookLM × Obsidian Second Brain

Use this skill for the workflow:

text
Capture → Digest → Distill → Apply → Review → Archive

NotebookLM is the temporary reading room, Obsidian/Markdown is the long-term vault, and the agent is the controlled organizer.

Hard boundaries

  • notebooklm-py is unofficial and uses undocumented Google NotebookLM APIs.
  • Never ask the user to paste storage_state.json, cookies, Google tokens, or browser session data into chat.
  • Never commit .notebooklm/, copied storage_state.json, .env, raw private documents, or generated private vault notes.
  • Require explicit user confirmation before uploading private/local documents to NotebookLM.
  • Require explicit confirmation before deleting notebooks/sources/artifacts, changing sharing settings, creating public links, or downloading artifacts into a project folder.
  • Prefer personal/local workflows. Do not package this as a SaaS that stores other people's Google sessions.

Install / verify

Project-local venv example:

powershell
python -m venv .venv-notebooklm
.\.venv-notebooklm\Scripts\python.exe -m pip install -U pip
.\.venv-notebooklm\Scripts\python.exe -m pip install "notebooklm-py[browser]"
.\.venv-notebooklm\Scripts\python.exe -m playwright install chromium
.\.venv-notebooklm\Scripts\notebooklm.exe --help

Auth must be performed by the user:

powershell
.\.venv-notebooklm\Scripts\notebooklm.exe login
.\.venv-notebooklm\Scripts\notebooklm.exe auth check --test --json

Treat auth as valid only if JSON contains:

json
{
"status": "ok",
"checks": { "token_fetch": true }
}

Safe CLI commands

Read/status commands are normally safe:

powershell
notebooklm auth check --test --json
notebooklm list --json
notebooklm status
notebooklm source list
notebooklm artifact list
notebooklm metadata --json

Write/external commands require confirmation:

powershell
notebooklm create "Notebook name"
notebooklm source add "file-or-url"
notebooklm ask -n <notebook_id> "question"
notebooklm generate quiz -n <notebook_id>
notebooklm download quiz -n <notebook_id> --format markdown output.md

Avoid shared context in parallel agents. Prefer explicit -n <notebook_id> instead of relying on notebooklm use.

Agent workflow

  1. Confirm scope:
  • source files / URLs
  • target vault folder
  • allowed outputs
  • forbidden directories/files
  • review criteria
  1. Capture:
  • create/select NotebookLM notebook
  • add only approved sources
  1. Digest:
  • ask NotebookLM for summaries, questions, key themes, gaps
  • optionally generate flashcards/quizzes/mind maps
  1. Distill:
  • do not paste NotebookLM output raw
  • rewrite into durable Markdown: MOC, concept cards, source cards, tasks, open questions
  1. Apply:
  • produce study plan / research plan / project handoff / quiz set
  1. Review:
  • mark uncertain claims
  • keep source references
  • list what needs human checking
  1. Archive:
  • leave raw imports or generated drafts in inbox/staging unless user approves promotion

Obsidian output pattern

Write to a reviewable inbox/staging area first:

text
<VAULT>/00_Inbox/
<VAULT>/10_Schoolwork/<Course>/
<VAULT>/20_Research/<Topic>/
<VAULT>/40_Projects/<Project>/AI_Handoff/

Each generated note should include:

markdown
---
type: notebooklm-digest
status: draft
source_tool: notebooklm-py
created: YYYY-MM-DD
review_required: true
---
# Title
## Source scope
## Summary
## Key concepts
## Evidence / citations to verify
## Flashcards or quiz items
## Open questions
## Next actions

MVP acceptance

A minimal successful run means:

  • notebooklm CLI installed and --help works
  • user completed notebooklm login
  • auth check --test --json passes
  • one test notebook is created or selected
  • one approved source is added
  • one question is asked successfully
  • one Markdown digest is written into the configured vault inbox/staging folder
  • no credentials or private source files are committed
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