Skip to main content
Glama
Crawlora-org

Crawlora MCP

Official
by Crawlora-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

fashionnova_product_recommendations

Fetch related or complementary Fashion Nova products by handle. Resolves handle to Shopify ID, returns up to 20 normalized recommendations.

Instructions

List Fashion Nova product recommendations. Returns normalized recommended products for one Fashion Nova (https://www.fashionnova.com) product handle. The route handle is resolved to a Shopify product id before fetching recommendations. The storefront URL is fixed server-side.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum products, defaults to 10 and supports up to 20
handleYesProduct handle
intentNoRecommendation intent. Allowed values: related, complementary

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / intent / enum
      Added value: +[
+  "related",
+  "complementary"
+]
  2. Addedv1.16.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does add useful context: outputs are 'normalized', the handle is resolved to a Shopify product id, and the storefront URL is fixed server-side. However, it does not mention auth requirements, rate limits, read-only nature, pagination, or the concrete response shape, leaving notable gaps.

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 description is three sentences with minimal waste and the core purpose is front-loaded. There is slight redundancy between 'List Fashion Nova product recommendations' and 'Returns normalized recommended products', but overall it is tight and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of both annotations and an output schema, the description should explain more about what a caller can expect. It covers the key input semantics and some internal behavior, but 'normalized recommended products' is vague and there is no detail on response contents, errors, or pagination, so it is adequate but incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema by explaining that 'handle' is a route handle resolved to a Shopify product id before fetching. That is genuinely useful semantic information for the one required parameter, even though limit and intent receive no additional explanation.

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?

The description states a specific action ('List Fashion Nova product recommendations') and identifies the exact resource (a Fashion Nova product handle), so an agent can tell it is a recommendations tool. However, it does not explicitly differentiate itself from the many sibling product recommendation tools or from fashionnova_product, so it falls short of full sibling differentiation.

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?

The description implies the tool is used when you have a Fashion Nova product handle and want recommendations, but it gives no explicit guidance on when to choose this over alternatives like fashionnova_product or other brand recommendation tools. There are no when-not-to-use conditions, prerequisites beyond the required handle, or references to sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools