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Comprar un estudio (pago x402)

comprar_estudio

PAGO por llamada en USDC (x402). Entrega el estudio: diseño del universo, hallazgos con su respaldo numérico y evidencia, métricas e índice de análisis, más links de descarga (7 días) al paquete completo con todas las tablas de análisis y las respuestas crudas de los modelos. Precios: banca-2026 USD 0.99, cadenas-hoteleras-cono-sur-2026 USD 0.99, cosmetica-2026 USD 0.99, dermatitis-atopica-2026 USD 0.99, farma-2026 USD 0.99, journey-gemelos-running-2026 USD 0.99, reumatologia-2026 USD 0.99, seguros-automotores-2026 USD 0.99, turismo-sierras-cordoba-2026 USD 0.99. Sin pago devuelve los requisitos x402; un cliente MCP con wallet x402 paga y reintenta solo. / Paid tool (x402): buy a full study.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesEstudio a comprar

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only flag readOnlyHint=false, openWorldHint=true, idempotentHint=false; the description adds substantial context beyond that: per-call USDC charging, exact price, the x402 challenge-and-retry flow, and the 7-day expiry on download links. It also discloses the full payload (tables plus raw model responses), which is exactly the kind of detail annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core is front-loaded and useful, but enumerating nine slugs each at 'USD 0.99' is pure padding that could be collapsed into one sentence. The trailing bilingual gloss ('/ Paid tool (x402): buy a full study.') is largely redundant with the opening line.

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

Completeness5/5

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

With no output schema, the description carries the return-value burden and does so: it names the deliverables, the download-link artifacts and their 7-day lifetime, and what comes back when payment is absent. Nothing needed to invoke or interpret the call is missing.

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 coverage is 100% and the single enum parameter is fully documented, so the baseline is 3; the description goes further by mapping each slug to its price, which is meaning the schema does not contain. The gain is modest because all nine prices are identical.

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?

States a specific verb+resource (comprar un estudio) and immediately frames it as the paid x402 purchase, which cleanly separates it from free siblings like ver_ficha, listar_estudios and buscar_estudios. The deliverables are enumerated, so an agent knows exactly what it is buying.

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?

Gives clear operative context: without payment the call returns x402 requirements, and an MCP client with a wallet pays and retries automatically — this tells the agent the call is safe to attempt blind. It never explicitly names an alternative (e.g. browse with listar_estudios/ver_ficha first), so it stops short of full when-not guidance.

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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