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maximeallanic

Carrefour Drive MCP

get_loyalty_order_receipt_details

Retrieve detailed Carrefour loyalty receipt for an in-store purchase using store GLN, date, and receipt number, including store name, total paid, discounts, barcode, and invoice links.

Instructions

Retrieves the detailed receipt for a specific in-store purchase associated with the authenticated user's loyalty card on Carrefour France. Returns receipt details such as store name, transaction date, total paid amount, discounts, receipt number, barcode, and links to invoice/card receipt. The receipt is identified by the store GLN, date key, and receipt number. (requires an authenticated Carrefour session)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glnYesThe GLN (Global Location Number) of the store where the purchase was made (e.g. '3020180204545')
date_keyYesThe date key of the transaction in YYYYMMDD format (e.g. '20260601')
receipt_numberYesThe receipt number identifying the specific transaction (e.g. '1-211-1907')
Behavior4/5

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

No annotations are present, so the description carries the burden. It discloses the authentication requirement and enumerates the returned fields (store name, totals, discounts, barcode, etc.), implying a read-only operation. It does not mention rate limits or error behavior, but for a retrieval tool this is adequate.

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 deliver all key information without fluff. The critical verb and resource are front-loaded.

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

Completeness4/5

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

Given three required parameters and no output schema, the description is sufficiently complete: it states the input identifiers, the return data categories, and the auth requirement. It lacks explicit error conditions, but they are not essential for basic invocation.

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?

Input schema already provides 100% parameter descriptions with examples, so the baseline is 3. The description adds context that the three parameters together identify a specific receipt, but no per-parameter semantics beyond the schema.

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?

Describes exactly what the tool does with a specific verb ('Retrieves') and resource ('detailed receipt for a specific in-store purchase'). It clearly differentiates from the sibling `get_loyalty_order_receipts` by focusing on a single receipt's details.

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?

Provides clear context: use when you have the GLN, date key, and receipt number for a specific in-store purchase. It does not explicitly mention alternatives or exclude `get_loyalty_order_receipts`, but the uniqueness of the identifiers makes the usage context clear.

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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