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paolodalprato

NotebookLM MCP Structured

search_notebooks

Search your notebook library by name, description, topics, or tags to find relevant notebooks for your task, then ask which to use.

Instructions

Search library by query (name, description, topics, tags). Use to propose relevant notebooks for the task and then ask which to use.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query
Install Server

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It adds useful context by explaining that results should be proposed and the user asked which to use, implying a non-destructive, candidate-returning search. However, it does not explicitly state that the operation is read-only, how results are returned, or any 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.

Conciseness5/5

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

Two short sentences, no filler, with the core function front-loaded. Every sentence earns its place: the first defines what it searches, the second defines how to use the results.

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?

For a single-parameter search tool with no output schema, the description covers the search fields and the intended follow-up workflow, which is enough to invoke correctly. It does not spell out the exact return structure, but that is a minor gap given the tool's simplicity.

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

Parameters4/5

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

The schema only describes 'query' as 'Search query', while the tool description adds that the query applies to name, description, topics, and tags. This enriches the otherwise minimal schema description and tells the agent what the query parameter will match.

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 states a specific action ('Search library by query') and defines the resource scope plus the fields being searched (name, description, topics, tags). This clearly distinguishes it from sibling tools like list_notebooks, which would list without query matching.

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

Usage Guidelines4/5

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

The description gives clear usage context: use it to propose relevant notebooks for the task and then ask which to use. It does not explicitly name alternatives or list when-not-to-use cases, so it stops short of a 5.

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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