create_support_ticketCreate a customer support ticket after signed-in browser approval.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | ||
| subject | Yes | ||
| order_id | No | ||
| confirmation_id | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
It discloses an important behavioral requirement beyond the annotations: signed-in browser approval is needed before the ticket is created. This meaningfully informs the agent that user interaction and authentication approval are required, even though the annotations themselves do not carry this context.
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 one tight sentence that front-loads the core action and includes the critical browser-approval prerequisite. There is no redundant restatement of the title or unnecessary filler.
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 tool with four parameters, two required, and zero parameter descriptions, the definition is thin. It does not explain the optional order_id and confirmation_id usage, possible behavior if browser approval is denied, or how the created ticket is returned. The presence of an output schema helps, but the surrounding context is still under-specified.
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 carries the burden of explaining parameters, but it mentions none. Property names like subject, message, order_id, and confirmation_id are somewhat self-explanatory, but the description does not clarify which fields are required, how they relate, or when the optional identifiers should be supplied.
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 uses a specific verb and resource: 'Create a customer support ticket.' It clearly identifies this as the tool for opening a new ticket, distinguishing it from siblings like reply_support_ticket, close_support_ticket, and list_support_tickets without ambiguity.
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 gives a clear operating condition: the ticket must be created after signed-in browser approval, which tells the agent this is not an unattended operation. It does not explicitly name alternatives or exclusions, but the creation intent is unambiguous given the sibling set.
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.