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hungln105-cell

notebooklm-mcp-cli

Chat Configure

chat_configure

Set notebook chat configuration: choose a goal, define a custom prompt, and adjust response length to tailor AI responses.

Instructions

Configure notebook chat settings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNodefault|learning_guide|customdefault
notebook_idYesNotebook UUID
custom_promptNoRequired when goal=custom (max 10000 chars)
response_lengthNodefault|longer|shorterdefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.11.5

TDQS

C2.9/5.0
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. 'Configure notebook chat settings' only vaguely implies a mutation; it does not state whether existing settings are overwritten, whether the change is persistent, what scope it applies to, or whether any side effects occur.

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 a single sentence with no filler and front-loads the action verb. It is concise, though the brevity sacrifices useful detail; structurally it is appropriate but not exemplary.

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

Completeness2/5

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

The tool has four parameters, a conditional dependency, and a large sibling context, but the description does not explain when to use it, what behavior to expect, or how it relates to other chat tools. With no annotations, this sparse description is insufficient for an agent to invoke the tool confidently in the right context.

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 schema already documents each parameter, including defaults and the conditional requirement for custom_prompt. The description adds no parameter-specific meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Configure') and identifies the resource ('notebook chat settings'), making the tool's broad function clear. It distinguishes itself from read-oriented siblings like chat_list and chat_get by implying a mutation or settings update, though it does not specify exactly which settings are affected.

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?

There is no guidance about when to use chat_configure versus alternatives such as chat_list, chat_get, or notebook_query. The description gives no prerequisites, such as requiring an existing notebook, nor does it explain conditional usage like needing custom_prompt when goal=custom.

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