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Validar en homologación

validar_en_homologacion

Validate an invoice by issuing it in homologation to get ARCA approval, then create a production-ready draft after passing checks.

Instructions

Valida la factura emitiéndola en homologación (sin valor fiscal) y, si ARCA la aprueba sin observaciones, crea un borrador listo para producción. Llamala solo después de que el usuario confirmó los datos. factura tiene el formato descripto en las instrucciones del servidor. punto_venta_homo sirve para esquivar el error de fechas de pruebas anteriores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
facturaYes
punto_venta_homoNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false. The description adds that it emits in homologation without fiscal value, conditionally creates a draft, and mentions a workaround for test dates. This provides behavioral context beyond annotations, such as the conditional draft creation and the non-idempotent nature implied by the action. No contradiction found.

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 three sentences long, each carrying value: the action and outcome, the usage condition, and parameter hints. It is concise and front-loaded, with no redundant information. It could be slightly more structured, but it is efficient.

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?

This is a mutation with conditional behavior, no output schema, and a nested parameter. The description explains the action and the conditional outcome (creates draft if approved) but does not specify what the tool returns, what happens if not approved, or how to interpret the result. It also lacks details on error handling and prerequisites beyond user confirmation. For a tool with this complexity, the description is incomplete.

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?

With 0% schema description coverage, the description must compensate. It states that `factura` follows the format described in server instructions (a pointer rather than a full explanation) and explains that `punto_venta_homo` is for avoiding previous test date errors. This gives some meaning but does not detail the structure of the nested factura object, leaving gaps for an agent.

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 validates an invoice by emitting it in homologation (test environment, no fiscal value) and conditionally creates a draft for production if ARCA approves without observations. It uses a specific verb (valida) and resource (factura) and distinguishes from siblings like emitir_en_produccion by specifying the homologation context.

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?

It explicitly instructs to call only after the user has confirmed the data, providing a clear when-to-use condition. It also explains the purpose of punto_venta_homo for avoiding date errors from previous tests. However, it does not explicitly mention alternatives or when not to use it, though the sibling context implies this.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.