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Crawlora MCP

Crawlora MCP

Official
by Crawlora-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

nike_suggest

Fetch Nike search-box typeahead suggestions for a partial query to find the exact phrases listed under Top Suggestions while typing.

Instructions

Get Nike search-box suggestions. Returns Nike's own search-box suggestions (typeahead) for a partial query, the same "Top Suggestions" list shown while typing into Nike's search box: a flat list of suggested search phrases, no product data.

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": {
      "query": "<query>"
    },
    "name": "nike_suggest"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesPartial search query

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.14.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden of explaining behavior. It discloses that the tool returns a flat list of suggested search phrases, not product data, and that suggestions mirror Nike's own Top Suggestions. This is meaningful behavioral context. It does not mention rate limits, authentication, or empty-result behavior, but for a read-only, simple suggestion tool this is a reasonable disclosure level.

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 two sentences with zero filler. It front-loads the exact action and resource, then provides the crucial scoping behavior—same Top Suggestions list, no product data. Every phrase contributes to helping the agent understand what the tool does and what it returns.

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 tool with one parameter, no annotations, and no output schema, the description is nearly complete: it explains what the return looks like ('a flat list of suggested search phrases'), how the suggestions relate to Nike's UI, and what is absent ('no product data'). It lacks an explicit return-item format or example, but this is a simple suggestion tool and the description provides enough to call it correctly.

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?

The schema already describes the only parameter, 'query,' with 'Partial search query' at 100% coverage. The description reinforces this by saying 'for a partial query' and phrases the tool as typeahead, but it does not add extra meaning such as minimum length, formatting, or examples. This matches the baseline score for full schema-documentation coverage.

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 uses a specific verb and resource: 'Get Nike search-box suggestions,' and further specifies it returns typeahead suggestions for a partial query—the same 'Top Suggestions' list as Nike's search box. It explicitly states 'no product data,' which clearly distinguishes it from nike_search and other product-focused tools without needing to inspect sibling schemas.

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?

The description gives clear context on when to use this tool: when you need Nike's search-box suggestions/typeahead for a partial query rather than full search results or product data. It does not explicitly name alternative tools like nike_search or say 'use nike_search for product results,' but the 'no product data' exclusion strongly implies the boundary. This is clear context without explicit exclusions.

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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