Save Pick
save_pickSave one visible saree to customer picks.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| saree_id | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
save_pickSave one visible saree to customer picks.
| Name | Required | Description | Default |
|---|---|---|---|
| saree_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey idempotence and non-destructiveness, lowering the burden on the description. The description adds a 'visible saree' precondition, but does not explain what happens if the saree is not visible or whether saving an existing pick is treated as an update.
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 with no filler or repeated information. It would benefit from defining 'visible,' but as a concise statement it is efficient.
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 the low complexity, one parameter, annotations, and an output schema, the description is reasonably complete. It still leaves the 'visible' rule unexplained and offers no direction about related pick-management tools, creating minor gaps for an agent.
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 0% schema description coverage, the description must compensate, and it does add minimal meaning by specifying 'one visible saree.' Still, it does not clarify where the saree_id should come from or elaborate on the 'visible' eligibility condition beyond the schema's generic ID pattern.
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 action ('Save'), a resource ('saree'), and a destination ('customer picks'), so an agent can understand the basic operation. However, it does not explicitly distinguish this tool from siblings like add_to_cart or remove_pick, and 'visible' is ambiguous.
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 given about when to use save_pick versus alternatives such as add_to_cart, get_picks, or remove_pick. The intended use is only implied by the phrase 'customer picks,' with no exclusions or context.
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.