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calcular_kilometraje

Read-only

Calcula la compensación o deducción fiscal por uso de vehículo propio en actividades económicas. Para empleados: exención IRPF hasta 0,26 €/km (RIRPF art. 9.B.2 — módulo AEAT 2025). Para autónomos: deducción en IRPF e IVA según exclusividad del uso del vehículo. Encadenable con calcular_irpf, calcular_cuota_autonomo, comparar_autonomo_vs_sl. Ideal para: "¿Cuánto me puedo deducir por usar el coche en el trabajo?" o "Mi empresa me paga 0,20€/km, ¿es correcto?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
perfilYes"empleado" = trabajador por cuenta ajena. "autonomo" = autónomo o profesional.
costeRealPorKmNoCoste real del vehículo por km (combustible, amortización, seguro, etc.) en euros. Por defecto 0,20 €/km.
tipoMarginalIRPFNoTipo marginal IRPF para calcular el ahorro fiscal en porcentaje. Por defecto 30%.
totalGastosVehiculoNoPara autónomos: total de gastos del vehículo en el año (combustible, seguro, reparaciones, amortización) en euros.
usoExclusivoActividadNoPara autónomos: ¿el vehículo está afecto exclusivamente a la actividad? (difícil de acreditar para turismos). Por defecto false.
kmProfesionalesAnualesYesKilómetros profesionales anuales (desplazamientos laborales o de la actividad económica).
compensacionRecibidaPorKmNoPara empleados: compensación que paga la empresa por km en euros. Por defecto 0.

TDQS

A4.2/5.0
Behavior4/5

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

The description adds value beyond the readOnlyHint annotation by explaining the tax rules, rates, and conditions (e.g., exclusivity for autónomos). It clarifies that the tool performs calculations based on inputs, which is consistent with a read-only operation. No contradictions with annotations.

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?

The description is two paragraphs with front-loaded purpose and legal references. It is relatively concise but could be slightly more concise by removing the example queries or legal citations. Structure is good, with clear separation of employee vs. autónomo use cases.

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

Completeness3/5

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

The description adequately explains the tool's purpose and parameters but does not specify the output format (e.g., what values are returned). Given the complexity and lack of output schema, more detail on return values would improve completeness. Still, the description provides sufficient context for a calculation 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?

The input schema already fully documents all 7 parameters with descriptions (100% coverage). The description provides high-level context about rates and legal references but does not add new parameter-level details. Baseline of 3 is appropriate as the schema does the heavy lifting.

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 calculates compensation or tax deduction for using a personal vehicle in economic activities, distinguishing between employees and autónomos. It provides specific legal references and example queries, making the purpose unequivocal and distinct from sibling tools.

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 states when to use the tool (for compensation/deduction calculations) and gives example queries. It also mentions it can be chained with other tools like calcular_irpf, indicating when not to use it alone. Additionally, it distinguishes scenarios for employees vs. autónomos, providing clear usage context.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools are cleanly separated by domain and purpose, but a few close pairs exist: calcular_camara_lenta and calcular_regla_180_video both touch the 180° shutter rule, and calcular_pace_running and calcular_prediccion_running both produce race projections. The descriptions are detailed enough to resolve the ambiguity, but misselection is possible if they are not read carefully.

Naming Consistency5/5

All tool names follow a consistent Spanish verb_noun snake_case pattern, with calcular_ dominating and the other verbs (convertir_, consultar_, recomendar_, escalar_) used for genuinely different action types. There is no mixed casing or style inconsistency.

Tool Count2/5

42 tools is far above the 25+ threshold and the set spans many unrelated domains such as cooking, fitness, photography, vehicles, dates, and finance. While each individual calculator may be useful, the server is not well-scoped and would be much easier to navigate if split into domain-specific MCP servers.

Completeness3/5

Coverage inside each sub-domain is quite thorough, but there are notable gaps: calcular_kilometraje references calcular_irpf, calcular_cuota_autonomo, and comparar_autonomo_vs_sl, none of which exist in this server. These dangling cross-references can lead an agent to attempt calling unavailable tools.

Resources