show_wishlistDisplay the authenticated user's saved wishlist items in a scrollable fashion carousel. Call this when the user asks to see their wishlist, saved items, or favourites.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds minimal behavioral context—only the 'scrollable fashion carousel' display format. This adds some value but doesn't disclose other traits like auth requirements (implied) or pagination, which are acceptable given the tool's simplicity.
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 two sentences, front-loaded with the purpose, and every word earns its place. No redundancy or unnecessary detail.
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 zero parameters, presence of annotations, and no output schema, the description fully covers what the tool does and when to use it. It is complete for its complexity level.
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?
The tool has zero parameters, so schema coverage is 100% trivially. The description doesn't need to add parameter details. According to guidelines, baseline is 3 for high coverage, but the absence of parameters makes the description's clarity sufficient for a 4.
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 clearly states the tool displays the authenticated user's saved wishlist items in a scrollable carousel. It identifies the specific resource (wishlist) and action (display). While it doesn't explicitly differentiate from sibling tools like get_user_looks, the context makes it distinct enough.
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 explicitly says 'Call this when the user asks to see their wishlist, saved items, or favourites,' providing clear usage guidance. It doesn't mention when not to use it or alternatives, but for a simple tool this is 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 target a clear resource (search, details, mix-and-match, wishlist, try-on), but search_fashion_products explicitly claims all styling/outfit requests while get_mix_and_match also handles outfit building, and both list 'what goes with my blue jeans' as an example. The selfie upload guidance also conflicts with try_on_product's built-in upload widget. Still, the detailed descriptions narrow most boundaries.
All names use snake_case and a verb-first pattern (get_, request_, search_, show_, try_on), making the set predictable. Minor inconsistency: get_mix_and_match and get_user_looks are less noun-like than the rest, and the retrieve-style verbs vary between get, show, and request.
8 tools is within the ideal 3-15 range and maps naturally to a shopping/styling assistant: search, detail, outfit, try-on, wishlist, saved looks, and uploads. No tool feels redundant enough to cut, and adding more would risk bloat.
The set covers the main shopper journey: search/browse, product detail, outfit building, virtual try-on, saved looks, and wishlist. The main gaps are wishlist mutation (add/remove) and an explicit way to manage/inspect selfies or context images, but these are workable around the existing tools.