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BeautySpark

Search BeautySpark (research)

search
Read-only

For research modes (deep research, company knowledge). In chat, use search_guides instead. Searches all public BeautySpark content: guide sections (id "/#"), article looks (id "look:") and colour-season palette pages (id "season:"). Read any result with fetch.

Input Schema

NameRequiredDescriptionDefault
queryYes
localeNoThe user's language as a language tag, e.g. "de" or "pt-BR". Set it from the user's language. Defaults to English.

Output Schema

NameRequiredDescriptionDefault
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the description's added value is the chaining instruction "Read any result with fetch" and the disclosure that only public content is indexed. It does not mention result limits, ranking, or pagination, which is the one remaining behavioral gap given an output schema exists.

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 tight sentences, no filler, and the when-to-use/alternative routing is front-loaded. The middle clause packing three id formats is dense but each format earns its place by enabling follow-up fetch calls.

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?

With an output schema present, the description need not explain return values, and it instead supplies the routing rule and id formats needed to chain into fetch. Only query semantics and any result-count limits remain unstated, which is a minor gap for a two-parameter search tool.

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 coverage is 50%: locale is documented in the schema while query is not, and the description does not explain query semantics (natural language vs keyword, whether it matches anchors or slugs). The id-format detail clarifies result structure rather than parameter meaning, so baseline 3 is appropriate.

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?

States a specific verb (searches) and enumerates the exact resource scope: guide sections, article looks, and colour-season palette pages, all public. The id formats ("<locale>/<slug>#<anchor>", "look:<id>", "season:<season>") make the result types concrete and distinguish it from search_guides and search_my_looks.

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 scopes usage to research modes (deep research, company knowledge) and names the alternative for the other case: "In chat, use search_guides instead." The public-only scope implicitly excludes search_my_looks, so an agent can route correctly without opening any schema.

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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