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Get product picks for a color season

get_product_picks
Read-only

BeautySpark's top product pick per category (blush, highlighter, eyeliner, lipstick, lip gloss, bronzer, eyeshadow palette) for a color season, each with the reason and the article it comes from.

Input Schema

NameRequiredDescriptionDefault
localeNoThe user's language as a language tag, e.g. "de" or "pt-BR". Set it from the user's language. Defaults to English.
seasonYesColor season, e.g. "True Winter" or "true_winter". One of the 12 seasons.
categoryNoOnly return picks of this category.

Output Schema

NameRequiredDescriptionDefault
picksYes
seasonYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds that results are a top pick per category accompanied by a reason and originating article, which is useful context, but it says nothing about result completeness, locale effects, or empty-result behavior beyond what annotations and output schema provide.

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?

A single front-loaded sentence with no filler; the core concept (top pick per category for a season) comes first and the output details follow. The parenthetical category list is somewhat redundant with the enum but still efficiently conveys scope.

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 simple read-only lookup with full schema coverage and an output schema, the description covers purpose, scope, and the shape of each result. It is essentially complete for correct invocation, though it could mention the sibling alternative to be fully self-sufficient.

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 three parameters are already documented, including the season format examples and locale behavior. The description only restates the category set already enumerated in the enum, adding little semantic meaning beyond the schema.

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 (get) and resource (top product pick per category for a color season), and enumerates the categories plus the fact that each pick includes a reason and source article. It does not explicitly distinguish itself from the sibling check_product_for_season, so it lands just short of 5.

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 description says what is returned but gives no when-to-use guidance, no conditions selecting it over siblings like check_product_for_season (which validates a specific product against a season), and no prerequisites. Usage is only inferable from the name and purpose sentence.

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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