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parfum1 Perfume API

Get a perfume

get_perfume
Read-onlyIdempotent

Read one perfume by its handle: name, house, description, top, heart and base notes, and every size (3, 10 and 30 ml) with the price, the struck regular price, price per ml and whether it is in stock, exactly as the product page shows them, plus the full bottle (listed out of stock) and the product URL.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "handle": "<handle>"
    },
    "name": "get_perfume"
  }
}

Input Schema

NameRequiredDescriptionDefault
handleYesThe perfume handle from search_perfumes, for example "hacivat-by-nishane".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, closed-world and non-destructive, so the bar is lower, yet the description adds real behavioral context: values are returned 'exactly as the product page shows them' (including struck regular price), and the full bottle variant is deliberately reported as out of stock. That pre-empts a plausible agent misreading. It does not mention failure behavior for an unknown handle, keeping it below a 5.

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

Conciseness4/5

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

One front-loaded sentence with the action first and the return payload after; no filler or hedging. It is dense and long, but every listed item corresponds to a value the agent needs since there is no output schema, so little could be cut without loss.

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?

With no output schema, the description carries the full return-value burden and discharges it: field list, all three sizes, price components, stock status, the out-of-stock bottle, and the product URL. Nothing an agent needs to decide whether this tool answers its question is missing.

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

Parameters3/5

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

Schema coverage is 100% and the single parameter already carries a pattern, length limit and a worked example ('hacivat-by-nishane'). The description only restates 'by its handle' and adds no format or sourcing detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Read one perfume by its handle') and enumerates the returned facets (name, house, notes, sizes, prices, stock, bottle, URL). This is unmistakably a single-item lookup, distinct from search_perfumes (multi-result) and get_house (different resource).

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

Usage Guidelines3/5

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

Usage is implied rather than stated: 'one perfume by its handle' signals a detail fetch following a search, and the schema note points at search_perfumes as the handle source. However, the description itself names no alternative and gives no explicit when-to-use or when-not-to-use rule.

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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