Read back one of YOUR checkout sessions by id: status, totals, line items, payment_handlers. Owner-scoped, so another agent's id returns not_found. REQUIRES IDENTITY on a signature-required Terminal.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The checkout session id. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It thoroughly discloses the return fields, owner-scoping with not_found behavior for foreign IDs, and the identity prerequisite. This is substantial transparency beyond basic read semantics.
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 three dense sentences with no redundancy. Each sentence contributes critical information (function, return fields, scope, auth requirement), making it highly efficient and well-structured.
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?
For a single-parameter read tool with no output schema, the description covers the return content, error behavior, and a prerequisite (identity). This gives an agent everything needed to invoke it correctly and anticipate results.
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?
The schema already covers the id parameter with 100% description coverage. The description enriches it by explaining owner-scoping and the not_found result for another agent's ID, which is meaningful context not present in the schema.
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 explicitly states the tool reads back a checkout session by ID and lists the returned fields (status, totals, line items, payment_handlers). This clearly distinguishes it from sibling getters like get_cart or get_order.
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 indicates the tool is owner-scoped ('another agent's id returns not_found') and requires identity on a signature-required Terminal, implying it is for one's own checkout sessions only. It does not explicitly name alternative tools, but the scope and resource make the usage context clear.
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.
