Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill blog-notebooklmgit clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-notebooklm)<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-notebooklm"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-notebooklm/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-notebooklm"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-notebooklm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00109 | $0.02050 |
| Opus 5 | $0.00055 | $0.01025 |
| Sonnet 5 | $0.00022 | $0.00410 |
| Haiku 4.5 | $0.00011 | $0.00205 |
Grade A, and why
blog-notebooklm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to blog-notebooklm — 36 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blog NotebookLM: Source-Grounded Research from Your Documents
Query Google NotebookLM notebooks directly from Claude Code for citation-backed answers from Gemini. Each question opens a headless browser session, retrieves the answer exclusively from your uploaded documents, and closes. Responses are Tier 1 quality (user's own primary sources): zero hallucination risk. Answers satisfy the FLOW evidence triple: use the returned source title as the inline citation and the notebook URL plus retrieval date as the bibliography entry. This is the highest-confidence path to meeting the "verified source" bar that FLOW requires before any statistic goes public.
Quick Reference
| Command | What it does |
|---|---|
/blog notebooklm ask <question> |
Query a notebook for source-grounded answers |
/blog notebooklm discover <url> |
Smart-discover notebook content before cataloging |
/blog notebooklm library list |
List all notebooks in library |
/blog notebooklm library add <url> |
Add a notebook to library |
/blog notebooklm library search <query> |
Search notebooks by keyword |
/blog notebooklm library remove <id> |
Remove a notebook from library |
/blog notebooklm setup |
One-time Google authentication (browser visible) |
/blog notebooklm status |
Check authentication status |
/blog notebooklm cleanup |
Clean browser state (preserves library) |
Prerequisites
- Google account with NotebookLM access
- Python 3.11+ (venv managed automatically by
run.py) - Google Chrome (installed automatically on first run via Patchright)
- One-time authentication setup (interactive Google login in visible browser)
Always Use run.py Wrapper
NEVER call scripts directly. ALWAYS use python3 scripts/run.py [script]:
# CORRECT:
python3 scripts/run.py auth_manager.py status
python3 scripts/run.py ask_question.py --question "..."
# WRONG -- fails without venv:
python3 scripts/auth_manager.py status
The run.py wrapper automatically creates .venv, installs dependencies,
sets up Chrome, and executes the target script.
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/commands.md 6.2 KB
- references/troubleshooting.md 4.3 KB
- scripts/__init__.py 3.3 KB runs code
- scripts/ask_question.py 9.8 KB runs code
- scripts/auth_manager.py 12 KB runs code
- scripts/browser_session.py 8.5 KB runs code
- scripts/browser_utils.py 4.5 KB runs code
- scripts/cleanup_manager.py 9.5 KB runs code
- scripts/config.py 1.6 KB runs code
- scripts/notebook_manager.py 14 KB runs code
- scripts/requirements.lock 6.6 KB
- scripts/requirements.txt 588 B
- scripts/run.py 2.9 KB runs code
- scripts/setup_environment.py 7.8 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 247 lines · 109 tokens per session scan A aaf4d8640ab3
blog-notebooklm is a skill published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 109 tokens to every session and 2,050 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to blog-notebooklm, differing in 36 lines, and is treated as a copy.
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