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blog-notebooklm

Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for source-grounded research context. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".

73

Quality

91%

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SecuritybySnyk

Critical

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SKILL.md
Quality
Evals
Security

Security

1 critical severity finding. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.

Critical

E004: Prompt injection detected in skill instructions.

What this means

Detected a prompt injection in the skill instructions. The skill contains hidden or deceptive instructions that fall outside its stated purpose and attempt to override the agent’s safety guidelines or intended behavior.

Why it was flagged

The skill contains explicit instructions and code to evade detection and persist automated access to Google NotebookLM (anti-detection patchright usage, cookie injection, persistent browser profiles, human-like typing/mouse simulation), which is suspicious steering that weakens security/bot-detection boundaries.

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Low

Low-risk findings.

1 low severity finding. Worth noting, but not necessarily harmful.

Low

W011: Third-party content exposure detected (indirect prompt injection risk).

What this means

The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.

Why it was flagged

The workflow reads untrusted free text via the user-supplied `--question` argument, which is typed into the NotebookLM web UI and then the resulting assistant text is extracted/ingested from the page during `ask_question.py` (query + response polling).

Repository
AgriciDaniel/claude-blog
Audited
Security analysis
Snyk

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