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Maison Éclaire

Get a Maison Éclaire product

get_product
Read-onlyIdempotent

Full details of one Maison Éclaire product by its slug (from search_products or a /produit/ URL): localized name and description, price and variant prices when in stock, photos and product URL. Always use image_url (or the Image: lines) from this tool for product photos; never use other images.

Input Schema

NameRequiredDescriptionDefault
langNoLanguage of names, descriptions, labels and URLs: fr (default), en or arfr
slugYesThe product slug, as in its URL /produit/<slug>

Output Schema

NameRequiredDescriptionDefault
urlYes
nameYes
slugYes
categoryYes
in_stockYes
variantsNo
image_urlYes
price_madNo
descriptionYes
old_price_madNo
price_is_fromNo
gallery_imagesNo
short_descriptionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
    • removedOutput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, closed-world, non-destructive, so safety is covered; the description adds genuinely new behavior: prices and variant prices appear only when in stock, and output is localized per language. It does not state what happens for an unknown slug, which keeps it from 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.

Conciseness5/5

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

Two sentences, front-loaded with identity and scope, followed by the image constraint. Every clause carries information: slug origin, returned fields, conditional pricing, image rule.

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 an output schema present and full schema coverage, the description only needs to add routing, conditional behavior and the image rule, and it does all three. Nothing an agent needs to call this correctly is missing.

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?

Schema coverage is 100%, so baseline is 3; the description earns above that by explaining where the slug comes from (search results or product URL) and by tying the lang parameter to localized names, descriptions and URLs. It does not restate the enum or pattern, but those are already fully documented.

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 ('Full details of one Maison Éclaire product by its slug') and immediately distinguishes it from the sibling search_products by naming that tool as the source of the slug. An agent can route between lookup and search without opening either schema.

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?

Gives explicit provenance for the required argument ('from search_products or a /produit/<slug> URL') and a firm conditional rule for images ('always use image_url ... never use other images'). It stops short of an explicit when-not clause (e.g., 'do not call for keyword browsing'), so it is strong routing guidance rather than a full decision 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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