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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context by indicating that the result is a suggestion scored with community compliment, office-safety, and versatility data, which helps an agent set expectations about the output and recommendation logic.

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 front-loaded sentence with no filler, stating the purpose before listing input factors and examples. It is slightly dense with parenthetical examples, but every component contributes to tool selection and invocation.

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 simple, read-only suggestion tool with all parameters optional and well-covered by the schema, the description is sufficient: an agent knows what inputs matter and what kind of output to expect. There is no output schema, but 'a fragrance suggestion' plus the scoring basis covers the essentials for a first call.

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%, and the schema already documents gender and season with useful descriptions. The description reinforces mood, occasion, and season as inputs and adds occasion examples, but it does not add significant semantics beyond what the schema already provides.

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 identifies the resource ('a fragrance suggestion') and the situational basis (mood, occasion, season), so an agent can understand what the tool produces. It does not explicitly differentiate from the sibling get_recommendations, but the 'for right now' framing and scoring criteria provide enough distinction for a 4.

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 gives a clear context for use: selecting a fragrance for the current moment based on mood, occasion, and season, with concrete occasion examples. It does not name alternatives or exclusions, but the situational trigger is reasonably explicit and actionable.

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