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Gemini Notebook (NotebookLM) MCP Server by useapi.net (third-party)

Update a source label

notebook_update_label
Idempotent

Rename a source label, change its emoji, and/or put sources of the same notebook under it or take them off; fields left out keep their values. Use it to fill a label made with notebook_create_labels name, or to correct Google's auto labels. The changes are applied one by one: if one fails, the error says how many went through. Returns the label with its name, emoji and source ids. POST /labels/{label}.

Input Schema

NameRequiredDescriptionDefault
nameNoNew label name.
emojiNoNew emoji for the label.
labelYesLabel id, from notebook_list_labels.
addSourcesNoSource ids of the same notebook to put under this label.
removeSourcesNoSource ids to take off this label (the sources stay in the notebook).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly=false, idempotent=true, destructive=false), but the description adds materially non-obvious behavior: omitted fields are preserved, mutations apply one-by-one, and a partial failure reports how many succeeded. It does not cover auth or rate limits, so it is strong on the failure semantics but not exhaustive.

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?

Front-loaded with the verb and resource, then layered with usage, failure behavior, and return value. Dense but each clause carries information; slightly long as a single paragraph but no filler.

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

Completeness5/5

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

For a 5-param mutation tool with no output schema, the description covers the operation, optionality, failure semantics, and even states the return shape (name, emoji, source ids). Nothing an agent needs to invoke it correctly is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema: 'fields left out keep their values' clarifies the optional/partial-update semantics, and the note that removed sources 'stay in the notebook' disambiguates removeSources from deletion.

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?

States a precise set of operations (rename, change emoji, add/remove sources) on a specific resource (source label), immediately distinguishing it from create/delete label siblings. An agent can tell it is a partial-update tool without opening the schema.

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?

Gives concrete use scenarios ('fill a label made with notebook_create_labels name', 'correct Google's auto labels') and names a sibling tool by name. It stops short of explicit when-not/alternative routing (e.g., delete_label vs this), so it is clear context rather than full when/when-not guidance.

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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