NotebookLM MCP Server

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 behavioral traits: the asynchronous nature (research_start -> poll research_status), time estimates (fast: ~30s, deep: ~5min), result volume estimates (~10 vs ~40 sources), and constraints (deep mode is web only). It doesn't mention error conditions or rate limits, but provides substantial operational context.

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 efficiently structured with clear sections (purpose, usage, workflow, args) and every sentence earns its place. It's front-loaded with the core purpose, followed by practical guidance, then detailed parameter explanations - all without wasted words.

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 complexity (5 parameters, asynchronous workflow, different modes/sources) and the presence of an output schema (which means return values don't need description), the description provides complete context. It covers purpose, usage workflow, parameter semantics, and behavioral expectations - everything needed for an agent to use this tool effectively.

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?

With 0% schema description coverage for 5 parameters, the description fully compensates by providing clear semantic explanations for all parameters: query purpose with examples, source options (web|drive), mode differences with timing/volume details, notebook_id behavior (creates new if not provided), and title purpose. This adds significant value beyond the bare schema.

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 ('search web or Google Drive to FIND NEW sources') and distinguishes it from siblings by mentioning the research workflow (research_start -> poll research_status -> research_import). It explicitly identifies the resource (sources) and differentiates from other tools like notebook_create or source_list_drive.

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 explicit usage guidance with 'Use this for:' examples ('deep research on X', 'find sources about Y', etc.) and a clear workflow sequence. It distinguishes when to use this tool versus alternatives by specifying the research workflow and mentioning source options (web/drive).

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