cancel_payment_attemptCancel an unpaid hosted payment attempt after signed-in browser approval.
| Name | Required | Description | Default |
|---|---|---|---|
| attempt_id | Yes | ||
| confirmation_id | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, readOnlyHint=false, and idempotentHint=false, so the description's main contribution is the 'unpaid' guardrail and the 'after signed-in browser approval' precondition. It does not disclose consequences such as whether a payment hold is released or whether cancellation is irreversible, but the annotation baseline lowers the bar.
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?
A single, front-loaded sentence with no filler. Every element—verb, resource, state, and precondition—carries meaning, and the structure makes the tool's purpose immediately scannable.
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 is adequate for an agent to know when selecting this tool and that attempt_id is the key input, especially with an output schema present. However, it leaves the optional confirmation_id undefined and does not explain how this cancellation relates to hosted-payment states or sibling resume/retry tools.
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% and the description adds no meaning for attempt_id or confirmation_id. The optional confirmation_id is left completely unexplained, and the description does not compensate for the schema's lack of parameter documentation.
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?
Description uses a specific verb ('Cancel'), a precise resource ('unpaid hosted payment attempt'), and a condition ('after signed-in browser approval'). It clearly distinguishes from sibling cancel_order by focusing on the payment attempt lifecycle.
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 clarifies that this applies only to unpaid hosted payment attempts and only after signed-in browser approval, which gives the agent useful selection context. However, it does not explicitly name alternatives like resume_payment or retry_payment or state when not to use it.
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.