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notebooklm

Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.

79

Quality

71%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./SKILL.md
SKILL.md
Quality
Evals
Security

Security

2 findings — 2 medium severity. This skill can be installed but you should review these findings before use.

Medium

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

Third-party content exposure detected (high risk: 0.90). The skill's scripts (e.g., scripts/ask_question.py and the SKILL.md/README) explicitly open arbitrary NotebookLM notebook URLs and scrape the NotebookLM responses (user-uploaded or web-sourced content) which the agent must read and use to drive follow-up queries and synthesize actions, so untrusted third‑party content can materially influence the agent.

Report incorrect finding
Medium

W012: Unverifiable external dependency detected (runtime URL that controls agent)

What this means

The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.

Why it was flagged

Potentially malicious external URL detected (high risk: 0.90). The skill programmatically opens and queries NotebookLM notebook URLs (e.g. https://notebooklm.google.com/notebook/...) at runtime (ask_question.py / Smart Add) and uses the returned notebook content to drive follow-up questions and final answers, so external content fetched from that URL directly controls agent prompts/behavior.

Repository
PleasePrompto/notebooklm-skill
Audited
Security analysis
Snyk

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