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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful behavioral context by naming the classification categories and the fact that it recommends a follow-up tool, which goes beyond the annotations. The lack of output-format detail is a minor gap.

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 a single concise sentence that front-loads the action and immediately states the classification categories and downstream recommendation behavior. There is no filler or redundant information.

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 classification and recommendation tool, the description covers what the tool does and what it returns conceptually: intent labels and a recommended next tool. With no output schema, a bit more detail about the exact response shape would be ideal, but the description is still sufficiently complete for an agent to invoke it correctly.

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 coverage is 100%: the single required 'query' parameter already has a description and an example. The tool description adds no further parameter-level detail, but none is necessary because the schema fully documents the parameter.

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 action: classify an academic question into four specific intents and recommend the next ssuMCP tool to invoke. This distinguishes it from sibling data-retrieval and action tools, which do actual lookups or mutations rather than routing and classification.

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 makes the usage context clear: it is for academic questions that need intent classification and downstream tool selection. It does not explicitly state when not to use it or name alternative classifiers, but its unique role as a routing/recommendation tool is implied well enough.

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