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jcrew_search

Search J.Crew or J.Crew Factory product catalogs by keyword and get product summaries with USD pricing, gender, description, and facet counts. Sort by price or relevance and filter by facet values.

Instructions

Search J.Crew or J.Crew Factory products. Searches the product catalog for either storefront (select with site, default jcrew). Returns 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 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

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

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does so well: it discloses the response shape (summaries + live-count facets), USD pricing, and critically the best-effort fallback behavior (obscure keywords return semantically-related results with no field distinguishing a true match). It does not cover auth/rate-limit behavior, but the fallback caveat is unusually valuable disclosure.

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?

Dense but front-loaded, leading with what it does before the mechanics. Every sentence carries information (storefront selection, return shape, sort, filter origin, fallback caveat), though the facet paragraph runs long.

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?

No output schema, so the description must describe returns and it does (summaries, USD pricing, facets with counts). All six params are effectively addressed and the fallback limitation is disclosed. Minor gaps remain around pagination semantics and auth, but the agent has enough to call it correctly.

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. The description adds real meaning beyond it: site default (jcrew), sort default (relevance), and most importantly that filter values must be drawn from a prior response's facets[].name/options[].value fields rather than a curated list. That provenance rule is not in the schema.

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?

Starts with a specific verb+resource ('Search J.Crew or J.Crew Factory products') and immediately disambiguates the two storefronts via the site parameter. An agent can tell exactly what catalog it operates over without opening the schema.

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?

Gives strong in-tool guidance: how to pick a storefront, that sort defaults to relevance, and how to construct filter values from a prior response's facets rather than a fixed list. It stops short of naming sibling tools (e.g. jcrew_category, jcrew_product) or stating when this search is preferable to browsing a category.

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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