Crawlora MCP

stevemadden_search_suggest

Read-only

Fetch Steve Madden predictive-search suggestions for an incomplete query, including products, collections, and query phrases. Use stevemadden_collections to browse collections or stevemadden_product for one known handle's details.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "stevemadden_search_suggest"
  }
}

Input Schema

Name	Required	Description
`q`	Yes	Required. Search query text.
`limit`	No	Maximum suggestions to return. Default 10, maximum 20.
`types`	No	Comma-separated suggestion types. Allowed values: product, collection, query. Defaults to product,collection,query.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and openness are covered. The description adds that results span products, collections, and query phrases, but says nothing about ordering, relevance, or rate limits beyond that.

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?

Two tight sentences: the capability comes first, then the disambiguation for siblings. No filler, no repetition of schema details.

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?

With an output schema present, return values need not be explained, and the annotations carry the safety profile. What remains is a basic, correctly scoped suggest tool; only return-ordering or relevance hints are missing, which is minor.

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 q, limit, and types are fully documented in the schema. The description's mention of products/collections/query phrases loosely maps to the types parameter but adds no syntax or default nuance beyond what the schema already provides.

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?

States a specific verb ('Fetch') and resource ('Steve Madden predictive-search suggestions'), scopes it to an incomplete query, and enumerates the returned entity kinds. It also names two siblings by function, so an agent can distinguish it from browse/detail tools immediately.

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

Usage Guidelines4/5

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

It explicitly routes to stevemadden_collections for browsing and stevemadden_product for a known handle, which covers the main alternatives. The positive trigger ('incomplete query') is stated but the when-not case is only implied by the alternatives rather than spelled out.

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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