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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds that the result is a curated set of 'picks' rather than a full listing, which is a useful behavioral trait, but it does not disclose return format, ordering, or any limitations. This is modest added context beyond the annotations.

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 sentence that front-loads the core purpose ('Personalized fragrance picks') and packs examples into parentheticals. It is information-dense but organized and not bloated, though it is slightly long relative to the unique value it adds over the schema.

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?

With no output schema and no explicit differentiation from sibling tools, the description leaves gaps: it does not explain what the returned recommendations look like or when to prefer this over find_similar or search_fragrances. Parameter constraints are fully covered by the schema and read-only annotations, so the essential calling contract is present, but the contextual gaps keep this below a 4.

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 parameters like preferences, budget, occasion, and gender already described with examples. The description provides some clearer example values for occasion and preferences, but it largely repeats schema information and does not significantly reduce reliance on the schema. Baseline 3 is appropriate.

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 a specific verb—'picks' as in recommends—and resource, 'fragrance picks,' while specifying the personalization inputs (preferences, budget, occasion, gender). This distinguishes it from generic search siblings, though it does not explicitly name any alternative.

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 implies the tool should be used when a user has note/accord preferences and optionally budget, occasion, or gender to get personalized fragrance suggestions. However, it offers no explicit when-to-use versus siblings like find_similar or trending_fragrances; the usage context must be inferred from the word 'personalized'.

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