Replace a cart's line items (full replacement), re-priced server-side. Owner-scoped. REQUIRES IDENTITY on a signature-required Terminal.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The cart id. | |
| line_items | No | The new full set of items, each `{ item: { id }, quantity }`. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It effectively communicates that the operation is a full replacement (not append), that prices are recalculated server-side, and that owner identity on a signature-required terminal is mandatory. This goes beyond a basic mutation statement, though it could mention side effects like error conditions.
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 a single, front-loaded sentence that states the action and follows with critical scoping/security caveats. There is no redundant or filler content.
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?
The description covers the core purpose, replacement behavior, repricing, ownership scope, and authentication requirement. However, the schema allows omitting line_items, and the description does not clarify what happens in that case (e.g., clears the cart vs. no-op), which is a minor gap. No output schema is provided, so absence of return-value details is acceptable.
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 description coverage is 100%, with both parameters clearly described. The description does not add parameter-specific meaning beyond the schema, so the baseline of 3 applies.
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 with a specific verb and resource: 'Replace a cart's line items (full replacement), re-priced server-side.' It also distinguishes itself from siblings like get_cart or create_cart by emphasizing full replacement and server-side repricing.
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 provides clear contextual prerequisites: 'Owner-scoped' and 'REQUIRES IDENTITY on a signature-required Terminal.' However, it does not explicitly name alternative tools or when not to use this tool, so it falls short of a 5.
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.
