claude-blog is a Claude Code skill suite for planning, writing, optimizing, auditing, localizing, and refreshing blog content. It is for content and SEO workflows that produce articles and related publishing artifacts while checking drafts against defined delivery criteria. The catalogue entries provide the skills, agents, plugins, and instruction used by this workflow.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/AgriciDaniel/claude-blognpx agentmods add skills/agricidaniel/claude-blog/blog-notebooklmWrote 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/agricidaniel/claude-blog/blog-notebooklm)<a href="https://agentmods.dev/skills/agricidaniel/claude-blog/blog-notebooklm"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-blog/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/agricidaniel/claude-blog/blog-notebooklm"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-blog/blog-notebooklm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.02141 |
| Opus 5 | $0.00055 | $0.01071 |
| Sonnet 5 | $0.00022 | $0.00428 |
| Haiku 4.5 | $0.00011 | $0.00214 |
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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- blog-notebooklm — 89% identical, 36 lines differ
How it starts
The opening of the file, as written. The whole thing — 255 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 from your uploaded documents, and closes. Responses are source-grounded model answers, not proof of truth: uploaded documents may be primary or secondary, and the answer can still omit context.
Answers satisfy the FLOW evidence triple only when the returned citation includes a verifiable underlying source URL plus a publication or retrieval date. Use the underlying source title as the inline citation. Do not cite the private NotebookLM URL as the bibliography entry for public content.
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 "..."
# Do not call files under scripts/ directly. The wrapper owns venv setup.
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.
- 11d ago First seen · 255 lines · 109 tokens per session scan A 22ca654bf5d3
blog-notebooklm is a skill published in the GitHub repository AgriciDaniel/claude-blog (2,116 stars, last pushed 7d ago), licensed MIT. It adds 109 tokens to every session and 2,141 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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