close_support_ticketClose a customer support ticket after signed-in browser approval.
| Name | Required | Description | Default |
|---|---|---|---|
| ticket_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 convey that this is a destructive, non-read-only, idempotent operation. The description adds one useful behavioral detail: it requires signed-in browser approval. However, it does not clarify what 'close' changes, whether the action is reversible, or how the approval/confirmation_id mechanism works.
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, tight sentence with no filler or redundancy. It front-loads the core action and resource, and every word adds meaning.
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?
Despite having an output schema and annotations, the description is too sparse for a destructive tool with an optional confirmation_id. It does not explain the approval flow, the meaning or requirement of confirmation_id, or the post-close behavior, leaving an agent without enough context to invoke the tool correctly in nuanced situations.
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 does not explain either parameter. 'Support ticket' weakly implies ticket_id identifies the ticket, but confirmation_id is completely unexplained and its relationship to 'signed-in browser approval' is left ambiguous.
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 identifies the action (close), the resource (customer support ticket), and a precondition (signed-in browser approval). It is not a tautology and is distinguishable from sibling tools like create_support_ticket or reply_support_ticket, though it does not explicitly name those alternatives.
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 'after signed-in browser approval' gives some contextual guidance about when this tool is appropriate, but it does not explicitly explain when to use it instead of related tools such as reply_support_ticket or cancel_order. No exclusions or alternative routing are provided.
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.