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harriedgemusic

NotebookLM MCP Server

generate_audio

Create audio overviews (podcasts) from NotebookLM notebooks by providing notebook IDs and custom instructions for podcast hosts.

Instructions

Generates an Audio Overview (podcast) for a notebook.

Args: notebook_id: The ID of the NotebookLM notebook. instructions: Custom instructions for the podcast hosts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
instructionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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. It states the tool generates audio, implying a creation/mutation operation, but lacks details on behavioral traits such as permissions required, processing time, rate limits, output format (though output schema exists), or whether it's destructive. This is inadequate for a tool with no annotation coverage.

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

Conciseness5/5

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

The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by a brief parameter explanation. Every sentence earns its place with no wasted words, and the structure is logical (purpose then args).

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

Completeness3/5

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

Given complexity (audio generation tool), no annotations, and an output schema (which handles return values), the description is minimally complete. It covers purpose and parameters but lacks behavioral context (e.g., processing details) and usage guidelines. With output schema reducing need for return value explanation, it's adequate but has clear gaps.

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 0%, so the description must compensate. It adds meaning by explaining 'notebook_id' as 'The ID of the NotebookLM notebook' and 'instructions' as 'Custom instructions for the podcast hosts,' which clarifies their roles beyond schema titles. However, it doesn't cover format details (e.g., ID structure, instruction length), leaving gaps. Baseline 3 is appropriate as it adds some value but not fully.

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: 'Generates an Audio Overview (podcast) for a notebook.' It specifies the verb ('Generates'), resource ('Audio Overview'), and target ('notebook'), distinguishing it from sibling tools like generate_video or generate_report. However, it doesn't explicitly differentiate from all siblings (e.g., generate_infographic or generate_slides) beyond the output type.

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 prerequisites (e.g., notebook existence), exclusions, or comparisons to siblings like generate_video or generate_report. The only implied usage is for creating audio content from a notebook, but no explicit context or alternatives are provided.

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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