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Gerar mapa mental

notebook_gerar_mapa_mental

Generate a mind map from selected notebook sources, returning a text tree and saving Markdown and JSON files for organizing ideas.

Instructions

Gera um mapa mental das fontes (~10-30 s) e devolve a árvore em texto; salva .md e .json. Os arquivos vão SEMPRE para /app/%LOCALAPPDATA%\mcp-google/saidas/notebooklm neste PC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focoNoTema ou recorte do mapa.
fontesNoUsar só estas fontes (títulos ou ids). Padrão: todas.
idiomaNoIdioma do resultado (ex.: pt-BR, en, es, fr, ou o nome como aparece no NotebookLM). Padrão: o do notebook (português).
notebookYesId, URL ou título do notebook (o título pode ser parcial).
uso_maximoNoTrava: não gera se o uso da IA (limite atual) passar desta % somando o estimado do item. Veja notebook_uso.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.16.1

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true), and the description adds valuable context: a 10-30s runtime and the fact that artifacts are ALWAYS written to a fixed local path. It does not state permission or auth requirements, which keeps it short of a 5.

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?

Two compact sentences that lead with the action and put the file-path caveat up front, with no filler. The Windows-style path with %LOCALAPPDATA% inside a POSIX-looking path is a bit confusing, but it is still brief.

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?

Without an output schema, the description carries the burden of defining the return, and it does (text tree plus saved .md/.json files), along with the timing and the fixed destination. For a five-parameter generation tool this is sufficient, though it could spell out what the returned tree contains or its size.

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 coverage is 100%, so every parameter is already documented in the schema, making the baseline 3. The description adds nothing about params beyond reiterating the file path destination and making no reference to foco, idioma, or uso_maximo semantics.

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?

States a specific verb and resource ("Gera um mapa mental das fontes") plus the output shape (tree returned as text, saved as .md/.json). It does not name which sibling studio generators it differs from, so an agent must infer the distinction from notebook_gerar_relatorio or notebook_gerar_infografico.

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

Usage Guidelines3/5

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

The mention of "fontes" and the file destination implies the generation context, but there is no explicit when-to-use, when-not-to-use, or which sibling generator to pick instead. The recommendation for uso_maximo points at notebook_uso, a small piece of routing, but overall usage is inferred rather than stated.

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