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set_refund_preference

Idempotent

For USDC orders: receive refunds as 'usdc' (sent to the paying wallet) or 'credit' (account credit).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodYes'usdc' sends refunds to the paying wallet; 'credit' adds them to account credit
order_idYesOrder id (ord_...) from list_orders or the paid quote

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the safety and repeatability profile is covered. The description adds genuine behavioral meaning by explaining where each refund route lands (paying wallet vs account credit), but says nothing about reversibility, timing relative to a refund event, or whether it is per-order or account-wide.

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?

A single sentence with the scope condition front-loaded and zero filler. It earns its place, though the value definitions duplicate what the enum descriptions already carry, so it is slightly redundant rather than maximally tight.

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

Completeness3/5

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

With an output schema present, return values need no explanation, and annotations plus full schema coverage carry the mechanics. What is still missing for a mutation tool is lifecycle context: whether the preference must be set before a refund is triggered and whether it can be overwritten later.

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 description coverage is 100%, and the schema already documents both the enum meanings and the order_id format. The description's parentheticals restate the same enum semantics rather than adding format, constraints, or defaults, so it is a baseline 3.

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

Purpose4/5

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

The description names the specific setting (refund preference), its applicable scope (USDC orders), and enumerates the two behaviors. An agent can tell this apart from every sibling, none of which touch refunds. It stops short of a clean verb+resource phrasing like 'Sets the refund preference for an order', but the intent is unambiguous.

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?

The qualifier 'For USDC orders' acts as an implicit precondition, telling the agent this tool is only relevant to USDC-paid orders. However, it gives no guidance on when to call it relative to the payment/refund lifecycle, whether it can be changed after being set, or what alternatives exist for non-USDC orders.

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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