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set2374

NotebookLM MCP Server

by set2374

notebook_get

Retrieve detailed information about a specific notebook, including its sources and content, by providing the notebook's unique identifier.

Instructions

Get notebook details with sources.

Args: notebook_id: Notebook UUID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves details, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns paginated results, or what 'details with sources' entails (e.g., structured data, metadata). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 concise and well-structured: a clear purpose statement followed by an Args section. It avoids unnecessary words and is front-loaded with the main functionality. However, the Args section could be integrated more smoothly, and it lacks additional context that might be helpful, slightly reducing efficiency.

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 low complexity (1 parameter, no nested objects) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the basic purpose and parameter, but gaps in usage guidelines and behavioral transparency prevent a higher score, as these are important for effective tool selection and invocation.

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?

The description adds minimal parameter semantics: it notes 'notebook_id: Notebook UUID' in the Args section, which clarifies the parameter's purpose and format. However, with 0% schema description coverage and only one parameter, this provides basic but not comprehensive insight. It meets the baseline since the schema covers the parameter's type and requirement, but doesn't add significant value beyond that.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Get notebook details with sources.' This specifies the verb ('Get'), resource ('notebook details'), and scope ('with sources'), distinguishing it from siblings like notebook_list (list notebooks) or notebook_describe (describe notebook). However, it doesn't explicitly differentiate from notebook_query, which might be a similar read operation, keeping it from a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like notebook_list (for listing notebooks) or notebook_describe (for describing notebooks), nor does it specify prerequisites such as needing a notebook_id. Without this context, the agent must infer usage from the tool name and description alone.

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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