notebooklm-mcp

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 describes what the tool does (downloads/exports content) and specifies return types (files for some, URLs for others), which adds useful context beyond the input schema. However, it lacks details on permissions, rate limits, error handling, or whether operations are idempotent, leaving gaps for a mutation tool.

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

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

The description is appropriately sized and front-loaded, starting with the core purpose, followed by a structured list of content types with clear outcomes, and ending with a concise note. Every sentence adds essential information without redundancy, making it efficient and easy to parse.

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

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

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is mostly complete: it covers the purpose, usage context, parameter semantics for content_type, and behavioral aspects like return types. However, it lacks details on error cases or prerequisites (e.g., authentication needs), which could be important for a download/export operation in this context.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds value by explaining the semantics of content_type options (e.g., 'audio_overview: Downloads as audio file (MP3)'), which clarifies beyond the enum list. However, it does not provide additional context for other parameters like output_path or notebook_url, so it meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('download' or 'export') and resources ('generated content from NotebookLM'), and distinguishes it from siblings by focusing on content retrieval rather than creation, management, or querying. It explicitly lists supported content types, making the scope unambiguous.

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

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 (e.g., for downloading audio, video, infographic, or exporting to Google Slides/Sheets) and includes a note that 'Report content is text-based and returned in the generation response,' implying an alternative (using generate_content instead). However, it does not explicitly state when not to use it or name specific sibling alternatives beyond this implication.

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