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shopify_search_suggest

Read-only

Returns products, collections, and query suggestions from Shopify's credential-free predictive search Ajax endpoint. q: Required. Search query text, e.g. wool. url: Required. Full Shopify storefront URL using http or https, e.g. https://www.allbirds.com. Localhost, private, link-local, and credentialed URLs are rejected. Use shopify_products to list Shopify products.

Input Schema

NameRequiredDescriptionDefault
qYesRequired. Search query text, e.g. wool.
urlYesRequired. Full Shopify storefront URL using http or https, e.g. https://www.allbirds.com. Localhost, private, link-local, and credentialed URLs are rejected.
limitNoMaximum suggestions to return. Default 10, maximum 20.
typesNoComma-separated suggestion types. Allowed values: product, collection, query. Defaults to product,collection,query.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds real behavioral context beyond that: it is credential-free, hits an Ajax endpoint, and rejects localhost, private, link-local, and credentialed URLs - concrete constraints an agent must respect on input.

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?

The purpose is front-loaded in the first sentence and every sentence carries information, though embedding parameter notes as inline prose makes it read as a run-on and duplicates schema content. No filler, but structure is slightly awkward.

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?

An output schema exists, so return values needn't be described, and annotations cover the safety profile. The description adds the endpoint nature, input URL constraints, and one routing hint, which is enough for a suggestion tool; only limit/types behavior is left entirely to the schema.

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 and url are already fully documented. The description merely restates those two parameters (with the same examples) and omits limit and types entirely, adding no meaning beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 ('Returns') and three concrete resources ('products, collections, and query suggestions') plus the exact source ('Shopify's credential-free predictive search Ajax endpoint'). It also names the sibling it is not ('Use shopify_products to list Shopify products'), so an agent can distinguish it without opening a schema.

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?

It provides one routing hint ('Use shopify_products to list Shopify products'), which implies a when-not, but the two tools are not clearly interchangeable and no conditions or prerequisites for choosing this tool are spelled out. Usage is only implied rather than explicitly framed as when-to-use vs when-not.

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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