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generar-prompt

Genera un prompt estructurado para una tarea de IA. input=descripción de la tarea. [x402: 0.01 USDC on Base, pay-per-use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesservice input

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It adds only that payment is 0.01 USDC on Base (pay-per-use) — a genuine behavioral/cost disclosure — but discloses nothing about output format, structure of the generated prompt, or limits.

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?

Compact, front-loaded: purpose, parameter hint, and payment note in one sentence plus bracket. No wasted words. The bracketed payment annotation is terse but integrated.

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?

One required parameter and no output schema make completeness easier to achieve. The description covers purpose, parameter meaning, and cost, but for a generation tool with no annotations it doesn't indicate output format or any variability in results, leaving the agent with a thin contract.

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 coverage is 100%, and the schema describes 'input' only as 'service input', which is uninformative. The description says 'input=descripción de la tarea', which actually clarifies the parameter's meaning beyond the schema's generic label — a modest improvement, but the schema itself is weak so the description only partially compensates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb+resource: 'Genera un prompt estructurado para una tarea de IA' states exactly what it produces and for what. No sibling differentiation, but among hundreds of siblings none obviously overlaps with prompt generation, so the purpose is identifiable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'para una tarea de IA' implies usage context (this is a meta-prompting/generation helper), and the payment note implies pay-per-use invocation. However, no explicit when-to-use vs alternatives or prerequisites are stated beyond the task description requirement.

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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