get_refund_by_store

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

Although no annotations are provided, the description details the underlying API calls (GET /v1/return_orders and GET /v1/orders/{order_id}) and the return structure, offering good insight into behavior. It does not mention permissions or rate limits, but the level of detail is sufficient.

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

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

The description is well-structured with sections for purpose, usage, API calls, and return structure. It is slightly verbose but clear and front-loaded with key information.

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

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

Given no output schema, the description provides a clear return structure (period, total_return_orders, stores with statistics). It covers the essential information, though details on pagination or limits are missing.

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

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

Schema coverage is 100% with descriptions for both parameters. The description adds no extra meaning beyond the schema; it only repeats that dates are in YYYY-MM-DD format. Baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose: analyzing return/refund distribution by store/channel. It specifies the action (get refunds by store), the resource (returns per store), and distinguishes from siblings like 'get_refund_summary' by focusing on store-level analysis.

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

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

The description gives context on when to use (for store-level return analysis within a date range) but lacks explicit guidance on when not to use or alternatives. Given the large sibling list, more differentiation would be helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.