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JavaScript
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fashionphile_search_suggest

Get search suggestions from Fashionphile's predictive search endpoint. Returns matching products, collections, and query suggestions in clean JSON for a given search term.

Instructions

Get Fashionphile search suggestions. Returns products, collections, and query suggestions from Fashionphile's (https://www.fashionphile.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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It adds genuinely useful behavioral context: the endpoint is credential-free (no auth needed) and the storefront URL is fixed server-side. It does not disclose rate limits, failure modes, or response shape, but the access model is clearly stated.

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 compact sentences front-load the purpose and output, then add differentiating endpoint facts. The parenthetical URL and server-side URL note earn their place by clarifying the data source and eliminating auth concerns.

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 suggest endpoint, the description gives the essential operational details: what it returns, that it is credential-free, and that the base URL is predetermined. Lacking an output schema, the return-value summary is high-level but sufficient for an agent to call it correctly; no major behavioral requirements are missing.

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 input schema already documents all three parameters (100% coverage). The description adds little beyond mapping the three returned suggestion types to the 'types' parameter, so it stays at the baseline 3.

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 names a specific verb and resource ('Get Fashionphile search suggestions') and explicitly states the returned entity types (products, collections, query suggestions). This distinguishes it from sibling fashionphile_search, which would return full search results, and from product/page tools.

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 description implies the use case—predictive/autocomplete suggestions—through the phrase 'predictive search Ajax endpoint,' but it never states when to prefer this tool over fashionphile_search or any other sibling, nor gives exclusion criteria. Selection relies on the tool name and inferred semantics.

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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