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JavaScript
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jcrew_search

Search J.Crew or J.Crew Factory products with sort and facet filters, returning normalized summaries with USD pricing, gender, and descriptions.

Instructions

Search J.Crew or J.Crew Factory products. Searches the product catalog for either storefront (select with site, default jcrew). Returns normalized product summaries with USD pricing, gender, and a description, plus the search index's own facets (gender, fabric, category, size, color, price range, and others) with live per-option counts. sort selects relevance (default), price_asc, or price_desc. filter narrows results by one or more facet name:value pairs (comma-separated, e.g. productGender:Men,styleFabric:Cashmere) taken from a prior response's own facets[].name/facets[].options[].value fields -- not curated against a fixed list, since the facet set is large and can change. This is best-effort relevance, not a guaranteed keyword match: for an obscure alphanumeric keyword the upstream search index falls back to its own semantically-related results instead of an empty list, and there is no reliable field in the response to distinguish a true keyword match from that fallback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoOne-based page
siteNoStorefront to search
sortNoSort order
filterNoComma-separated facet name:value pairs, e.g. productGender:Men,styleFabric:Cashmere
keywordYesSearch keyword
per_pageNoResults per page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / site / enum
      Added value: +[
+  "jcrew",
+  "factory"
+]
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "relevance",
+  "price_asc",
+  "price_desc"
+]
  2. Addedv1.16.0

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: it mentions normalized product summaries, USD pricing, gender, description, facets with live counts, and the best-effort relevance with fallback to semantically-related results. This is exceptionally transparent.

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 comprehensive yet concise, front-loading the core purpose and providing necessary details in a structured flow. Every sentence adds value, with no redundancy.

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

Completeness5/5

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

Even without an output schema, the description covers what the response contains (product summaries, pricing, facets) and important caveats (fallback, no reliable match indicator). It is complete for an agent to call the tool appropriately.

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

Parameters5/5

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

Although schema coverage is 100%, the description adds significant meaning: it explains the 'site' enum meaning, sort behavior, filter syntax with an example, and that filter values come from prior response facets. It goes beyond the schema by specifying how parameters interact.

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 states a specific verb ('Search') and resource ('J.Crew or J.Crew Factory products'), and clarifies the storefront selection via 'site' parameter. It distinguishes itself from sibling tools like jcrew_categories and jcrew_product by focusing on catalog search.

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

Usage Guidelines5/5

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

Explicitly explains when to use this tool (searching products) and provides key usage details: site defaults to jcrew, sort options, filter syntax, and how filters are derived from prior responses' facets. It also warns about the fallback behavior, giving clear guidance on interpreting results.

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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