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JavaScript
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stevemadden_search_suggest

Fetch Steve Madden predictive search suggestions for products, collections, and queries by entering a search term, with optional result limits and type filters.

Instructions

Get Steve Madden search suggestions. Returns products, collections, and query suggestions from Steve Madden's (https://www.stevemadden.com) predictive search. The storefront URL is fixed.

Input 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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that results are predictive and that the storefront URL is fixed (so no URL parameter is needed), which is useful context, but it does not state that this is a read-only operation, describe pagination/limits behavior, or characterize the response shape beyond the three suggestion types.

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

Conciseness4/5

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

Three short sentences, front-loaded with the purpose, and no wasted filler. The final sentence about the fixed storefront URL earns its place since there is no URL parameter, though it is slightly redundant.

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, low-complexity suggest tool with no output schema and full schema coverage, the description is largely complete: it conveys purpose, the three result categories, and the fixed-source constraint. Minor gaps around read-only safety and result limits remain, but nothing critical is missing for correct invocation.

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 description coverage is 100%, so the schema already documents q, limit (default 10, max 20), and types (product, collection, query). The description reinforces that products/collections/query are the return categories, giving a slight hint about the types parameter, but adds no syntax or format detail beyond the schema. Baseline 3 is appropriate.

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

Purpose4/5

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

States a specific verb+resource (search suggestions) and clarifies what is returned: products, collections, and query suggestions via predictive search. This distinguishes it reasonably from siblings like stevemadden_products or stevemadden_collections, though it doesn't explicitly name those alternatives.

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

Usage Guidelines2/5

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

There is no explicit when-to-use vs when-not guidance and no alternatives named, despite many sibling tools (stevemadden_products, stevemadden_collections, stevemadden_search-adjacent). The predictive/autocomplete use case is only implied by 'suggestions'.

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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