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JavaScript
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farfetch_search

Search Farfetch listings by department with a required designer or category filter, returning normalized summaries (name, brand, price, image, availability) and page count.

Instructions

Search Farfetch listings. Browses Farfetch's luxury multi-brand marketplace by department plus a designer and/or category filter (at least one is required), returning normalized listing summaries (name, brand, price, image, availability) and the upstream page count. Public data sourced from Farfetch's own listing pages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page number; defaults to 1
genderYesDepartment: women, men, kids
categoryNoCategory slug from GET /farfetch/categories; designer or category is required
designerNoDesigner slug from GET /farfetch/designers; designer or category is required

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that data is public, that results are normalized summaries, and that it returns the upstream page count. It does not mention rate limits or error handling, but for a read-only search this is adequate.

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 sentences with no fluff. The purpose, return type, and data source are all front-loaded. Every clause earns its place.

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 search tool with 4 documented parameters and no output schema, the description covers the return type (normalized summaries, page count) and source, which is sufficient for an agent to invoke it correctly. It could mention pagination behavior but the page parameter is already explained in 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 all four parameters are documented. The description repeats the designer/category requirement already present in the schema, adding little new semantic value beyond summarizing the filter logic.

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 clearly states a specific verb (search), resource (Farfetch listings), and scope (by department with optional filters), and distinguishes from sibling tools like farfetch_product (single product) and farfetch_categories/designers (which provide slugs). It also specifies the return type (normalized listing summaries).

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?

The description explicitly states the requirement that a designer or category filter is needed, and that it browses the marketplace. However, it does not name alternative tools (e.g., farfetch_categories for fetching slugs) to steer the user, relying on the parameter descriptions for that guidance.

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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