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AleWWH1104

Skincare Recommendation MCP Server

by AleWWH1104

check_ingredient_conflicts

Compare active ingredients between a candidate product and your current routine to reveal potential conflicts before use.

Instructions

Check whether a candidate product's active ingredients conflict with ingredients the client already uses.

Args: current_ingredients: active ingredients in the client's current routine. candidate_ingredients: active ingredients of the product being considered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
current_ingredientsYes
candidate_ingredientsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. 'Check whether' strongly implies a read-only, non-destructive operation, and the parameter descriptions clarify what is being compared. However, it does not state whether any data is modified, whether authentication is required, or how conflicts are determined.

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 compact and well organized: a single purpose sentence followed by a clear Args list. No redundant phrasing or unnecessary detail; every sentence 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?

Given the simple parameter signature, the presence of an output schema, and no nested objects, the description covers the essential context. It leaves minor gaps around how conflict results are represented, but those are presumably satisfied by the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does so by explaining both parameters in plain language: current_ingredients are the client's active ingredients and candidate_ingredients are those in the product under consideration. This adds meaningful semantic value beyond the bare array-of-strings schema.

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 states a precise action—'Check whether'—against a specific resource: ingredient conflicts between a candidate product and the client's current routine. This clearly separates it from sibling tools like search_products or recommend_products, which serve different functions.

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 establishes clear context: use it when evaluating a candidate product against the client's current ingredients. It does not explicitly name alternatives or state when not to use it, but the use case is obvious enough that an agent can route to it appropriately.

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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