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AlanGr12

sportlink-mcp

by AlanGr12

calcular_match

Calculate the compatibility percentage between an athlete and a sport opportunity by comparing sport, age category, and geographic zone.

Instructions

Calcula el porcentaje de compatibilidad (match) entre un atleta y una oportunidad (prueba/entrenamiento).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
edadAtletaNoEdad del atleta
zonaAtletaNoZona geográfica del atleta
categoriaMaxNoEdad máxima permitida
categoriaMinNoEdad mínima requerida
deporteAtletaYesDeporte principal del atleta
zonaOportunidadNoZona geográfica de la oportunidad
deporteOportunidadYesDeporte requerido en la oportunidad

Schema Changelog

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

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description must carry the full burden of behavioral disclosure, but it only says 'calcula', giving no information about side effects, required context, return format, or how the match is computed. The tool appears non-destructive, but that is inferred rather than documented.

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 a single, focused sentence that immediately communicates the core purpose. It avoids fluff and is well-structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple in concept but has 7 parameters, no annotations, and no output schema; the description does not explain the expected result format or how to interpret the percentage. This leaves significant gaps for an agent that needs to invoke it correctly and use its output.

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 baseline is 3 even though the descriptions are terse labels like 'Edad del atleta'. The tool description itself adds no parameter-level insight beyond what the schema already provides.

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 function: calculating a compatibility percentage between an athlete and an opportunity. It is specific and distinct from the sibling tools, which are search and profile viewing operations.

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 gives no guidance on when to use this tool versus alternatives, nor does it mention prerequisites such as having an athlete profile or opportunity details. It only implies a general use case through the phrase 'entre un atleta y una oportunidad'.

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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