notebooklm-mcp

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the search scope (name, description, topics, tags) but doesn't describe important behavioral aspects like whether this is a fuzzy or exact match search, how results are ranked/limited, authentication requirements, or error conditions. The description adds some value but leaves significant gaps for a search operation.

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 exceptionally concise and well-structured. The first sentence clearly states the core functionality, and the second sentence provides practical usage guidance. Every word earns its place with zero redundancy or wasted space.

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?

For a search tool with no annotations and no output schema, the description provides adequate but incomplete coverage. It explains what the tool does and when to use it, but lacks details about result format, pagination, error handling, or performance characteristics that would be important for an AI agent to use it 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?

Schema description coverage is 100% with a single 'query' parameter documented in the schema. The description adds marginal value by specifying what fields the query searches against (name, description, topics, tags), but doesn't provide additional syntax, format, or constraint details beyond what the schema already indicates. This 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: searching a library by query across multiple fields (name, description, topics, tags). It specifies the verb 'search' and resource 'library/notebooks', but doesn't explicitly differentiate from sibling tools like 'list_notebooks' or 'get_notebook', which reduces it from a perfect score.

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 usage context: 'Use to propose relevant notebooks for the task and then ask which to use.' This gives practical guidance on when to employ this tool in a workflow. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the many sibling tools.

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