set_cart_quantitySet quantity for one customer cart item.
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | ||
| quantity | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=false, idempotentHint=true, and destructiveHint=false, and the description is consistent with them (no contradiction). The phrase 'Set quantity' usefully implies overwriting the existing quantity rather than incrementing it. However, it does not disclose prerequisites, ownership/authentication requirements, or error behavior when the item is absent.
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 seven-word sentence with the verb front-loaded and no filler words. It is efficient and scannable, though the brevity borders on under-specification given the 0% schema parameter coverage.
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 simple two-parameter setter with an output schema and safety annotations, the description is minimally adequate. The main gaps are the absence of usage context relative to the closely related cart siblings and the ambiguous meaning of item_id. Since an output schema exists, the lack of return-value documentation is not penalized.
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 full burden. It loosely maps 'quantity' and 'cart item' to the two parameters, but it does not clarify whether item_id refers to a product ID or a cart line-item ID, nor does it explain that quantity is an absolute value (1–20) replacing the current quantity. This leaves an agent guessing.
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 states a specific verb ('Set') and a precise resource ('quantity for one customer cart item'). It clearly scopes the action to a single cart item, which implicitly distinguishes it from siblings like add_to_cart and remove_from_cart. However, it does not explicitly name or contrast those alternatives, so differentiation relies on inference.
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?
No guidance is provided on when to use this tool versus add_to_cart, remove_from_cart, or get_cart. There are no stated prerequisites (e.g., the item must already exist in the cart) and no exclusion conditions. An agent must infer the use case entirely from the title and sibling names.
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.