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

Annotations already cover the read-only, idempotent, non-destructive profile, so the description's main job is to add behavioral context. It does this by disclosing the return type: most relevant classes with confidence scores and explanations. This goes beyond the annotations and gives the agent a useful expectation of the output.

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?

Two short, front-loaded sentences with no filler. The first sentence states the core function, and the second discloses the output format. Every word earns its place.

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 read-only recommendation tool with a simple two-parameter schema, the description is largely complete: it states the input basis, the output shape, and the relevance framing. It could be slightly richer about the exact format of the returned classes, but the annotations and schema cover most operational needs.

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 baseline is 3. The description doesn't add much parameter meaning beyond the schema; it implicitly reinforces that business_description is the core input but doesn't explain industry usage or output structure beyond what is already stated.

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 uses a specific verb ('Recommend') and resource ('Nice trademark classes'), and clarifies the basis ('business description'). It also differentiates from sibling tools like get_nice_classes by noting it returns ranked, relevant classes with confidence scores and explanations.

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 clearly signals when to use this tool: when the user provides a business description and needs class recommendations. It doesn't explicitly state when not to use it or name alternatives, but the context is clear enough for an agent to select it over lookup-style tools like get_nice_classes.

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