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thebodyshop_search_suggest

Retrieve The Body Shop predictive search suggestions for a query, returning products, collections, and related query matches.

Instructions

Get The Body Shop search suggestions. Returns products, collections, and query suggestions from The Body Shop's (https://www.thebodyshop.com) predictive search. The storefront URL is fixed server-side.

Input Schema

NameRequiredDescriptionDefault
qYesSearch query
limitNoMaximum results per type, defaults to 10 and supports up to 20
typesNoComma-separated suggestion types. Allowed values: product, collection, query

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden but partly meets it: it discloses that the storefront URL is fixed server-side (so no domain parameter is needed) and describes what categories of suggestions come back. It does not mention auth requirements, rate limits, or whether the call is read-only (implied by 'Get'), leaving meaningful 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?

Three compact sentences with the core purpose front-loaded ('Get The Body Shop search suggestions'), followed by return contents and a useful scoping note. No filler or repetition, though the URL parenthetical is slightly verbose.

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?

There is no output schema or annotation coverage, so the description must stand alone. It adequately describes the suggestion types returned but is thin on operational context for a 3-parameter tool, and does not clarify how results are structured or ordered.

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 the schema already documents q, limit (default 10, max 20), and types (product, collection, query). The description's mention of 'products, collections, and query suggestions' lightly mirrors the types parameter but adds no syntax or behavioral detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Get The Body Shop search suggestions') and goes further to describe the return contents: products, collections, and query suggestions via predictive search. This lets an agent distinguish it from a full product search, though it doesn't explicitly contrast it with siblings like thebodyshop_products or the many other *_search_suggest tools.

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 word 'predictive search' hints at autocomplete-style usage, but there is no explicit guidance on when to choose this over thebodyshop_products or a full search, and no stated prerequisites or exclusions. The agent must infer its role entirely from the name and phrasing.

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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