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content_download

Idempotent

Save NotebookLM generated content: download audio, video, infographics as files, or export presentations and data tables to Google Slides and Sheets.

Instructions

Download or export generated content from NotebookLM.

Supported content types:

  • audio_overview: Downloads as audio file (MP3)

  • video: Downloads as video file

  • infographic: Downloads as image file

  • presentation: Exports to Google Slides (returns URL)

  • data_table: Exports to Google Sheets (returns URL)

Note: Report content is text-based and returned in the generation response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
content_typeYesType of content to download/export
output_pathNoOptional local path to save the file (for audio, video, infographic)
notebook_urlNoNotebook URL. If not provided, uses the active notebook.
session_idNoSession ID to reuse an existing session

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successYesWhether the tool call succeeded.
dataNoThe tool payload on success. The exact shape depends on the tool.
errorNoHuman-readable error message, present only when success is false.
Behavior4/5

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

The description adds behavioral context beyond annotations: it specifies that presentations and data_tables return URLs rather than files, and notes that report content is text-based and returned in generation response. Annotations already indicate idempotent and non-destructive, so the description complements them.

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 concise, well-structured with bullet points, and front-loads the purpose. Every sentence is informative and earns its place, with no wasted words.

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?

Given the complexity (4 parameters, 1 required, enum) and presence of an output schema (though not detailed here), the description covers the main aspects: purpose, types, output formats, and a note about reports. It could include a brief mention of the return structure, but overall it is sufficiently complete.

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%, but the description adds meaning by clarifying that output_path is only applicable for audio, video, and infographic types, which is not evident from the schema alone. It also lists the enum values with output formats, enhancing understanding.

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?

The description clearly states 'Download or export generated content from NotebookLM' and enumerates all supported content types with their output formats, distinguishing it from sibling tools like content_generate (creation) and content_list (listing).

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?

The description explains when to use the tool (to download/export generated content) and lists supported types with output details. It implicitly guides usage by noting that 'report' content is not downloadable here, but does not explicitly state when not to use or compare to alternatives.

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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