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notebooklm_upload_sources

Upload website URLs or files to a NotebookLM notebook for AI-powered analysis. Creates the notebook automatically if it doesn't exist.

Instructions

Upload sources to a NotebookLM notebook.

Uploads website URLs or files to a specified notebook. Creates the notebook if it doesn't exist.

Source types:

  • website: Provide a URL

  • file: Provide an absolute file path (PDF, TXT, etc.)

Example sources: [ {"type": "website", "value": "https://example.com/article"}, {"type": "file", "value": "/path/to/document.pdf"} ]

Limits: ~500KB per source, 50-300 sources per notebook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_nameYesName of the notebook (created if not exists)
sourcesYesArray of sources to upload
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: the tool performs write operations (uploading, creating notebooks), specifies source types and formats, provides concrete examples, and discloses important limits (~500KB per source, 50-300 sources per notebook). This covers most essential behavioral aspects for an upload tool.

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 well-structured and efficiently organized: it starts with the core purpose, explains parameters with clear examples, and ends with important limits. Every sentence adds value without redundancy, making it easy to parse while being comprehensive.

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?

For a tool with no annotations and no output schema, the description does an excellent job covering the essential context: purpose, usage, parameters, examples, and limits. The main gap is the lack of information about return values or error conditions, but given the tool's complexity and the absence of structured output documentation, this is reasonably complete.

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?

The schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds some value by explaining what 'sources' should contain (with examples and type details) and clarifying that 'notebook_name' triggers creation if non-existent, but doesn't provide significant additional semantic context beyond what's in the schema.

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 the specific action ('Upload sources') and resource ('to a NotebookLM notebook'), with explicit details about source types (website URLs or files) and notebook creation behavior. It distinguishes itself from sibling tools like 'notebooklm_list_notebooks' or 'notebooklm_prepare_content' by focusing on upload functionality.

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 provides clear context for when to use this tool (uploading website URLs or files to a notebook) and mentions that it creates the notebook if it doesn't exist. However, it doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools, though the context is sufficiently clear for typical usage scenarios.

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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