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boots_suggest

Get Boots UK search-box suggestions for partial product queries, returning typeahead phrases to use with boots-search for product cards and facets.

Instructions

Get Boots UK search-box suggestions. Returns Boots UK's own public typeahead phrases for a partial product query. The suggestions are search terms only; pass one to boots-search's q parameter for product cards and live facets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesPartial product query

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.2

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description must disclose behavior. It states that the tool returns search terms only and that they are public typeahead phrases, which is somewhat informative. However, it does not specify the format of the response (e.g., array of strings), possible rate limits, or whether the suggestions are based on real-time data. This is a relatively simple read-only tool, but without annotations, the description could add more about response structure or potential missing suggestions.

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 very concise (two sentences) and front-loads the main purpose. It avoids redundant wording and includes only essential information, making it efficient for an agent to read and understand quickly.

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?

This is a simple tool with one parameter and no output schema. The description covers the purpose, input, and how to use the output, which is largely sufficient. The only minor omission is lack of detail on the exact return format on failure or empty responses, but given the simplicityebates and clear guidance, it is close to complete.

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%: the only parameter 'q' is described as 'Partial product query'. The description elaborates that the query is for a product and that suggestions are typeahead phrases, which adds some context beyond the schema. However, it does not specify required format, length constraints, or examples, so the added value is modest.

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 the tool's purpose: getting Boots UK search-box suggestions for a partial product query. It specifies the source (Boots UK's own public typeahead), the output type (search terms only), and differentiates it from related tools like boots_search for product cards. This is a specific verb-resource pair with clear scope.

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?

The description explicitly explains how to use the results: pass a suggestion to boots-search's q parameter for product cards and facets. This gives clear guidance on the workflow and distinguishes this tool from alternatives, as it is for getting suggestions, not for direct product search.

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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