update_profileUpdate customer name, phone, and delivery address after signed-in browser approval.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| phone | Yes | ||
| address | Yes | ||
| confirmation_id | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that this is a write operation to specific profile fields and adds a key behavioral detail not present in annotations: a signed-in browser approval is required. Annotations already provide idempotentHint=true and destructiveHint=false, and the description does not contradict them.
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 that conveys the action, object, and precondition with no filler. Every word adds meaningful guidance, making it an efficiently structured definition.
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?
Given a simple 4-parameter update with an output schema present, the description covers the essential purpose, the main parameters, and the approval precondition needed to invoke the tool correctly. The only notable gap is the unexplained confirmation_id parameter, which is optional and therefore does not block correct invocation.
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?
With schema_description_coverage at 0%, the description compensates partially by explaining the semantics of three parameters: name, phone, and delivery address. However, the optional confirmation_id parameter is not mentioned at all, leaving the agent without insight into its role as an approval token or idempotency identifier.
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 opens with 'Update customer name, phone, and delivery address,' naming a specific verb, resource, and target fields. The title 'Update Profile' reinforces the resource, and since no sibling tool handles profile updates, the purpose is unambiguous despite not naming a differentiating alternative.
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' states a concrete precondition for invoking the tool, giving the agent a clear gate for when it is appropriate. It does not describe alternatives or when-not-to-use scenarios, but the lack of any competing profile-update sibling makes this context sufficient.
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.