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etsy_search_orders

Retrieve orders created in a date window for a shop. Optionally filter by status and set a maximum number of results. Pagination is handled automatically.

Instructions

Search receipts (orders) created in the inclusive [date_from, date_to] window for a shop.

Args: date_from: ISO date (YYYY-MM-DD), start of window. date_to: ISO date (YYYY-MM-DD), end of window. shop_id: Etsy ShopID to scope the search to. Falls back to ETSY_DEFAULT_SHOP_ID if omitted. status: Optional receipt status filter ('open', 'unshipped', 'unpaid', 'completed', 'processing', 'all'). limit: Cap on yielded receipts (default 200, max 1000). Etsy caps page size at 100 per request; pagination is handled transparently.

Returns: JSON envelope. data.orders is the list of receipt records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
date_fromYes
date_toYes
shop_idNo
statusNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description carries full burden. It discloses transparent pagination handling, limit cap (1000, with 100 per page), default shop_id fallback, and return format. It does not mention read-only nature or rate limits, but for a search tool the disclosed behaviors are substantial.

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?

The description is well-structured with a summary sentence followed by bullet-pointed parameter details. Every sentence adds value, no redundancy. It is concise yet comprehensive, fitting all necessary information into a compact format.

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?

Given the output schema exists (not shown but indicated), the description adequately covers return structure ('JSON envelope with data.orders'). All parameters, default behaviors, and pagination are explained. No critical gaps remain for a search tool with moderate complexity.

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

Parameters5/5

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

The description adds extensive meaning beyond the input schema: date format (ISO), inclusive window semantics, shop_id fallback to ETSY_DEFAULT_SHOP_ID, status enum values, limit with transparent pagination. Schema coverage is 0%, so description fully compensates, making each parameter's purpose and constraints clear.

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 clearly states it searches receipts/orders by date window for a shop. 'Search receipts (orders) created in the inclusive [date_from, date_to] window for a shop.' is a specific verb+resource+scope. However, it does not differentiate from sibling tools like etsy_get_order or etsy_search_listings, leaving ambiguity about when to use this versus alternatives.

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 description implies usage for searching orders within a date range, with optional filters. Yet it provides no explicit guidance on when not to use it or references to sibling tools for alternative use cases. The context of searching by shop and date window is clear but lacks exclusionary criteria.

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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