Side-by-side comparison: note pyramids, shared and distinct accords, longevity/sillage/compliment scores, concentration, and price difference.
| Name | Required | Description | Default |
|---|---|---|---|
| fragrance_a | Yes | First fragrance — slug or name | |
| fragrance_b | Yes | Second fragrance — slug or name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that the tool is read-only, idempotent, and non-destructive. The description adds the core behavioral context: exactly what dimensions the comparison covers. It does not explain edge cases like missing fragrance data, but for a safe read-only comparison this is strong additional context.
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?
A single, tightly written sentence that front-loads the operation and then uses a colon-separated list to convey the comparison scope. No redundant words or filler.
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?
This is a low-complexity two-parameter tool with strong read-only annotations and no output schema. The description adequately conveys what the result will cover and the pair being compared. It lacks explicit alternativ routing, but the operation is clear enough to invoke 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?
The input schema already documents both parameters with 100% coverage, including that each accepts a slug or name. The description does not add parameter-specific details, which is acceptable since the schema carries the burden.
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 operation as a side-by-side comparison and enumerates concrete comparison dimensions: note pyramids, shared/distinct accords, longevity/sillage/compliment scores, concentration, and price difference. This distinguishes it from sibling tools like get_fragrance or find_similar, which are single-fragrance or similarity-focused tools.
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 phrase 'side-by-side comparison' implies the tool should be used when a user wants to compare two fragrances, and the parameter names make the pair explicit. However, it does not mention when to prefer this over siblings like find_similar or find_dupes, nor any when-not conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools have clearly distinct purposes: search, detail, comparison, similarity, dupes, recommendations, trends, and situational suggestions. The main potential confusion is between find_similar and find_dupes, since both return fragrances related to a given one, though their intent differs.
Tool names mostly follow a verb_noun snake_case pattern: compare_fragrances, find_similar, get_fragrance, search_fragrances. trending_fragrances and what_to_wear_tonight break the verb-first convention slightly, but the overall naming style is coherent and readable.
Eight tools is well-scoped for a fragrance discovery and recommendation service. Each tool covers a distinct user need without redundancy or bloat, and the count feels appropriate for the domain.
The tool set covers the full fragrance journey: searching, retrieving details, comparing, finding alternatives, personalized recommendations, trend awareness, and context-based picks. There are no obvious dead ends or critical missing operations for a read-focused recommendation API.