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skims_search_suggest

Fetch product, collection, and query suggestions from SKIMS predictive search. Use it to power autocomplete and show relevant options for a given search query.

Instructions

Get SKIMS search suggestions. Returns products, collections, and query suggestions from SKIMS's (https://skims.com) credential-free predictive search Ajax endpoint. The storefront URL is fixed server-side.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query
limitNoMaximum results per type, defaults to 10 and supports up to 20
typesNoComma-separated suggestion types. Allowed values: product, collection, query
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden and does disclose meaningful traits: the endpoint is credential-free, implying no authentication is required, and the storefront URL is fixed server-side, so no URL configuration is needed. The 'Get' wording and 'predictive search' context convey a read-only operation, though rate limits and error behavior are not covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three short sentences, front-loaded with the action and return values, followed by endpoint characteristics. Every sentence earns its place and there is no redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only suggest tool with one required parameter and full schema coverage, the description is essentially complete: it names return categories, states no credentials are needed, and clarifies the fixed URL. It could go slightly deeper on response shape, but no output schema exists and the high-level return types are stated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents q, limit, and types with defaults, maximums, and allowed values. The description adds only a marginal high-level mapping of return categories to the types parameter rather than any essential parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with a specific verb and resource — 'Get SKIMS search suggestions' — and further specifies the output as products, collections, and query suggestions from a predictive search Ajax endpoint. This clearly differentiates it from sibling tools that retrieve full product or collection data rather than typeahead suggestions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The intended use is implied: call this when predictive search or autocomplete suggestions for SKIMS are needed. However, the description gives no explicit when-to-use guidance, exclusions, or alternatives such as skims_products or skims_collections.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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