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".
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Low
Low-risk findings worth noting
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
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.
Source text is outsider-authored when it comes from the user-supplied `question` passed into `scripts/run.py ask_question.py --question "..."` and from any user-provided `--notebook-url` during `/blog notebooklm ask`/`/blog notebooklm discover`, which the workflow then feeds into Google NotebookLM (via a headless browser session) for source-grounded answers.
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.
The skill accepts and queries NotebookLM notebook URLs at runtime (e.g., https://notebooklm.google.com/notebook/...), fetching notebook content that is injected into the agent's responses and thus can directly control prompts.
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