get_oms_orderFull detail for one fulfillment order: line items (SKU, qty, picked/reserved), lifecycle history (state transitions with timestamps), credit consumption, pickup slot, and resolved shipping city/state. Get the id from search_oms_orders.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The OMS order id. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds valuable context by detailing what the response includes (line items, lifecycle transitions, credit consumption). This goes beyond the structured fields and helps the agent understand the scope of the read operation.
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 two sentences, front-loaded with the core purpose ('Full detail for one fulfillment order'), then efficiently lists the key data categories. No filler or redundant information appears.
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?
With a single parameter, output schema present, and annotations covering safety, the description provides sufficient context. It names the source for the id and the specific detail areas, making the tool's behavior clear without needing extra explanation of return format (handled by output schema).
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 id described as 'The OMS order id.' The description adds the crucial guidance to obtain this id from search_oms_orders, providing practical source information that the schema alone does not convey. This elevates the baseline from 3 to 4.
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 provides 'Full detail for one fulfillment order' and enumerates specific fields (line items, lifecycle history, credit consumption, etc.). This distinguishes it from sibling tools like get_order or search_oms_orders by focusing on a single OMS fulfillment order with complete details.
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 explicitly instructs the user to 'Get the id from search_oms_orders', providing a concrete workflow for retrieving the required parameter. It implies use for single-order detail but does not explicitly state when to prefer this over alternatives like get_order.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct data points (e.g., get_analytics_summary vs get_brand_score). However, 'search' and 'search_catalog' have overlapping functionality and could cause confusion, and 'fetch' is a helper tied to 'search', adding minor ambiguity.
The majority use consistent verb_noun snake_case (e.g., get_inventory, list_stores). Exceptions like 'fetch' and 'search' (without object) break the pattern, but they are few.
43 tools is excessive for a data-retrieval-only API. Many get_* and search_* tools could be consolidated (e.g., search_catalog, search_inventory, search_orders are similar). The large number will overwhelm an agent.
The tool set is entirely read-only (get, search, list, fetch). There are no create, update, or delete tools, which is a critical gap for managing e-commerce operations. Agents can only view data, not act on it.