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notebooklm

notebooklm

by dfelix-net
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

generate_audio_overview

Generates a podcast-style audio summary for a NotebookLM notebook, with optional instructions to guide the discussion.

Instructions

Gera um Resumo em Áudio (podcast) no NotebookLM.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "notebook_id": "<notebook_id>"
    },
    "name": "generate_audio_overview"
  }
}

Input Schema

NameRequiredDescriptionDefault
notebook_idYes
instructionsNoCrie um podcast de análise aprofundada.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries the full burden and discloses almost nothing behavioral. It does not indicate whether generation is asynchronous/long-running, whether it overwrites prior audio, what permissions are required, or what the result looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

A single front-loaded sentence with no wasted words, which is good. However, it is so terse that it under-specifies the tool rather than being genuinely 'concise', and it omits any structure that would aid invocation.

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?

For a generative tool with no annotations, no output schema, and 0% parameter coverage, the description is far too thin. It omits prerequisites, expected behavior, and return characteristics that an agent needs to call it correctly.

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

Parameters2/5

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

Schema description coverage is 0% and the description explains neither parameter. It never clarifies that notebook_id identifies the target notebook or that instructions customizes the podcast content, leaving both the required and optional parameters undocumented.

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: generates an 'Audio Overview' (podcast) in NotebookLM. It is distinguishable from close siblings like generate_video_overview and generate_mind_map by naming the audio/podcast output, though it offers no further differentiation among the family of generate_* tools.

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?

No guidance on when to use this versus alternatives such as generate_video_overview or get_notebook_summary, and no statement of prerequisites (e.g., that the notebook must already contain sources). Usage must be fully inferred.

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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