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notebook.ask

Ask questions to NotebookLM to retrieve answers from your documentation, with session support for context and customizable source citations.

Instructions

Conversational Research Partner (NotebookLM • Gemini 2.5 • Session RAG)

No Active Notebook

  • Visit https://notebooklm.google to create a notebook and get a share link

  • Use add_notebook to add it to your library (explains how to get the link)

  • Use list_notebooks to show available sources

  • Use select_notebook to set one active

Auth tip: If login is required, use the prompt 'notebooklm.auth-setup' and then verify with the 'get_health' tool. If authentication later fails (e.g., expired cookies), use the prompt 'notebooklm.auth-repair'.

Tip: Tell the user you can manage NotebookLM library and ask which notebook to use for the current task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesThe question to ask NotebookLM
session_idNoOptional session ID for contextual conversations. If omitted, a new session is created.
notebook_idNoOptional notebook ID from your library. If omitted, uses the active notebook. Use list_notebooks to see available notebooks.
notebook_urlNoOptional notebook URL (overrides notebook_id). Use this for ad-hoc queries to notebooks not in your library.
show_browserNoShow browser window for debugging (simple version). For advanced control (typing speed, stealth, etc.), use browser_options instead.
source_formatNoFormat for source citation extraction (default: none). Options: - none: No source extraction (fastest) - inline: Insert source text inline: "text [1: source excerpt]" - footnotes: Append sources at the end as footnotes - json: Return sources as separate object in response - expanded: Replace [1] with full quoted source text Note: Source extraction adds ~1-2 seconds but does NOT consume additional NotebookLM quota.
browser_optionsNoOptional browser behavior settings. Claude can control everything: visibility, typing speed, stealth mode, timeouts. Useful for debugging or fine-tuning.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successYesWhether the tool call succeeded.
dataNoThe tool payload on success. The exact shape depends on the tool.
errorNoHuman-readable error message, present only when success is false.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnlyHint=false and idempotentHint=false, and the description adds context about session-based RAG and stateful conversations. It also mentions that source extraction adds time but not quota. No contradictions; however, it could further disclose error handling or authentication failure behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with markdown sections, but is slightly verbose with tips and redundant advice (e.g., 'Tip: Tell the user...'). It front-loads key information but could be trimmed for better conciseness without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters with nested objects) and the presence of an output schema, the description adequately covers the overall flow and prerequisites. It mentions source format options and session management but omits details on error scenarios. Still, it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The tool description does not add meaning beyond the schema's detailed parameter descriptions; it only provides usage context. Thus, scoring at baseline is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a conversational research partner for asking questions to NotebookLM. It specifies the action ('ask a question'), the resource (NotebookLM), and distinguishes from sibling tools by outlining prerequisites and alternative tools like add_notebook, list_notebooks, and select_notebook.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance, including prerequisites (e.g., having an active notebook), and suggests alternatives when conditions are not met. It also includes an auth tip and a tip for user interaction, giving clear context for usage vs. other tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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