get_checkout_summaryRevalidate cart, discounts, points, addresses, and checkout total without placing an order.
| Name | Required | Description | Default |
|---|---|---|---|
| coupon_code | No | ||
| points_to_redeem | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds useful behavioral nuance by saying it 'revalidates' checkout data and explicitly does not place an order, which goes slightly beyond the generic annotation hints.
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 with no filler. It communicates the core action, scope, and side-effect boundary efficiently.
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 an output schema and strong annotations, the description does not need to explain return values or safety. However, it lacks explicit routing guidance against sibling tools and leaves the optional parameters only minimally described, so it is adequate but not fully complete.
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 0%, so the description must compensate, but it only loosely references 'discounts' and 'points'. It does not explain how coupon_code and points_to_redeem are applied, whether they are independent or interactive, or what validation semantics apply.
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 names a specific verb ('Revalidate') and a clear resource scope (cart, discounts, points, addresses, checkout total), and explicitly excludes order placement. This clearly distinguishes it from order-placing siblings like start_checkout.
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 phrase 'without placing an order' implies this is a pre-checkout validation/preview tool, but the description does not explicitly explain when to use it instead of related siblings such as get_cart, validate_coupon, or start_checkout. The use case is implied, not stated.
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 are clearly separated by resource and action (cart, orders, tickets, picks, payments), so an agent can generally select the right one. The only notable ambiguity is resume_payment vs retry_payment, which both describe acting on an unpaid hosted payment attempt with nearly identical wording.
All 29 tools follow a consistent snake_case verb_noun (or verb_preposition_noun) pattern with standard verbs like get, list, create, close, remove, and set. There are no mixed conventions or vague generic names.
At 29 tools this is a heavy surface, but the broad e-commerce scope (catalog, cart, checkout, payment, orders, support, rewards) justifies most of them. A few payment-attempt tools could be consolidated, so it sits at the overbuilt rather than absurdly bloated end.
The set covers the main customer journey from browsing/searching sarees through cart, checkout, payment status, orders, and post-purchase support. Minor gaps exist—for example, no explicit apply_coupon/redeem_points tool or standalone catalogue listing—but agents can work around them with validate_coupon, checkout summary, and search.