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 effectively communicates that this is a write operation ('Add notebook'), requires explicit user permission ('Only after explicit "Yes"'), and has specific workflow constraints (the mandatory conversation steps). However, it doesn't mention potential side effects like rate limits, authentication requirements, or error conditions that might be relevant for a tool that adds data to a library.

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?

While well-structured with clear sections, the description is excessively long (over 400 words). Much of the content (like the detailed 'How to Get a NotebookLM Share Link' section and extensive example) could be streamlined or moved elsewhere. The core information about the tool's purpose and usage is front-loaded, but the overall length reduces efficiency.

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 complexity of a 7-parameter write operation with no annotations or output schema, the description does a good job of providing context. It covers the tool's purpose, when to use it, a detailed workflow, rules, and an example. However, it lacks information about what happens after successful execution (return values or confirmation) and doesn't address potential error scenarios or system limitations.

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?

The input schema has 100% description coverage, so the schema already documents all 7 parameters thoroughly. The description doesn't add any additional semantic context about the parameters beyond what's in the schema descriptions. It references some parameters indirectly in the workflow (URL, description, topics, use cases) but doesn't provide new information about their meaning or usage.

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: 'Add notebook with manually specified metadata' and explicitly distinguishes it from its sibling 'auto_discover_notebook' in the very first line. It specifies the verb ('Add'), resource ('notebook'), and scope ('manually specified metadata'), making it immediately distinguishable from alternatives.

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 extensive and explicit guidance on when to use this tool versus alternatives. It includes a dedicated 'When to Use' section with three specific scenarios, a 'Conversation Workflow' that mandates trying auto_discover_notebook first, and explicit rules like 'Prefer auto_discover_notebook when possible' and 'Do not add without user permission.' This gives the agent clear decision criteria.

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