get_support_ticketGet one authorized customer support ticket and its messages.
| Name | Required | Description | Default |
|---|---|---|---|
| ticket_id | Yes |
| 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, non-destructive behavior. The description adds that the response includes associated messages and that access is limited to authorized tickets, which is useful but modest given the existing annotation coverage.
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 sentence that front-loads the verb and resource with no filler. It is appropriately sized for a simple read operation.
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 one-parameter read tool with rich annotations and an output schema, the description covers the essential scope: a single authorized ticket plus its messages. Nothing an agent needs to select or invoke it correctly is missing.
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 needed to compensate for the ticket_id parameter, but it never mentions its format, source, or constraints. The schema provides pattern and length rules, but the description adds no semantic value for parameter handling.
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?
States a specific action ('Get') on a specific resource ('one authorized customer support ticket') and notes it includes messages, clearly differentiating from list/create/close/reply support ticket tools. The singular 'one' signals it is not list_support_tickets.
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 implies usage when a single ticket with messages is needed, but it does not explicitly say to use list_support_tickets for multiple tickets or to avoid this tool in other cases. No when-not or alternative routing guidance is 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.