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get_fragrance

Read-onlyIdempotent

Detailed record for one fragrance: full note pyramid (top/heart/base), accords, concentration, community longevity/sillage/compliment scores, and MSRP. Accepts a Perfume Picks slug or a name like 'Bleu de Chanel'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slug_or_nameYesFragrance slug or name

TDQS

A4.3/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so no safety contradictions exist. The description adds meaningful scoping context by stating it returns a 'detailed record for one fragrance' and listing the output attributes, which clarifies the tool's behavior beyond a generic getter. It does not disclose edge-case behavior (e.g., handling of ambiguous names or not-found errors), but the annotations lower the bar.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, each earning its place: the first lists the record's contents, the second specifies the input format. No filler or repetition of schema/annotation data.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter, read-only retrieval tool with no output schema, the description covers both invocation (slug or name) and expected return contents (note pyramid, scores, MGRP). No critical information is missing for an agent to successfully call it, and annotations already provide the safety profile.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents the slug_or_name parameter with 100% coverage, so the baseline is 3. The description adds a concrete example ('Bleu de Chaanel') and clarifies that a slug must be a 'Perfume Picks slug', giving the agent a better sense of the accepted format than the schema's generic 'Fragrance slug or name'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Detailed record for one fragrance', which specifies the verb (get) and resource (fragrance) precisely. Listing the full note pyramid, accords, concentration, community scores, and MSRP distinguishes it from siblings like search_fragrances or compare_fragrances, which operate on lists or multiple items. This makes the tool's purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes it clear this is for retrieving a single fragrance's detailed record, so an agent can infer when to use it: when a specific fragrance is already known. It does not explicitly name alternatives or say when not to use it, such as 'for browsing, use search_fragrances'. However, the contextual clue 'one fragrance' versus the sibling names implies the appropriate use case.

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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TDQS

A4/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count5/5

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.

Completeness5/5

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.