Read back one of YOUR orders on this merchant: status, amount, settlement state. Use the order_id returned when you paid. You can only read orders your own agent identity placed — another agent's order returns FORBIDDEN. REQUIRES IDENTITY: Facet KYA as Authorization: Bearer <kya>.
| Name | Required | Description | Default |
|---|---|---|---|
| order_id | Yes | The order id returned at payment. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It discloses that the tool is read-only, returns specific fields, enforces agent-level access control (FORBIDDEN for other agents), and requires a specific authentication mechanism (Bearer KYA). All behavioral traits are explicitly stated.
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?
Three sentences, each serving a distinct purpose: purpose, constraints, authentication. No wasted words; critical information is front-loaded.
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 adequately lists return fields (status, amount, settlement state) and mentions error behavior (FORBIDDEN). The single parameter is explained, and authentication requirement is specified. Complete for an agent to correctly invoke the tool.
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% (one parameter fully described). The description adds minor context (order_id returned when you paid) but does not significantly add beyond the schema description. 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 reads back one of YOUR orders on this merchant, specifying the returned fields (status, amount, settlement state). It distinguishes from siblings like list_orders by emphasizing that it retrieves a specific order using order_id and only for the agent's own orders.
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?
Provides explicit when-to-use (to read back an order using the order_id from payment), when-not-to-use (another agent's order returns FORBIDDEN), and prerequisites (identity required with Authorization header). No alternative tools mentioned but clearly delineates scope.
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 map to a distinct lifecycle step, and the detailed descriptions separate discovery, cart, checkout, payment, order, and wishlist concerns well. However, get_product and lookup_catalog are largely the same lookup by identifier, discover_products and search_catalog overlap across scope, and update_checkout is actually a read-only no-op.
The set overwhelmingly follows a verb_noun pattern: create_cart, get_checkout, cancel_checkout, complete_checkout, search_catalog. Minor deviations are the wishlist_* resource-first subgroup and the misleading update_checkout, which does not perform an update.
At 23 tools, this sits at the heavy end of the range, though the broad commerce lifecycle does justify substantial surface area. The count is inflated by redundant product lookup tools and a no-op update_checkout, so a more trimmed set in the low-to-mid teens would be healthier.
The server covers the full shopper lifecycle well: discovery, product lookup, cart, checkout, payment, order placement, order read, refunds, and wishlist. Gaps are minor and workable, such as update_checkout not actually supporting updates and no explicit order-cancellation path once a checkout is complete.
