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Ficha de una lección

ver_leccion
Read-onlyIdempotent

Ficha pública de una lección: resumen, objetivos, secciones, tiempo de lectura, cómo se accede y URL. No devuelve el cuerpo de la lección. Úsala para explicar qué enseña una lección sin necesidad de cuenta. Para el texto completo, usa leer_leccion (pide iniciar sesión y acceso al nivel) o enlaza la URL. Si el slug no existe, llama a ver_temario para ver los válidos.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesSlug de la lección, hasta 80 caracteres: «05-herramientas» en el Básico o con el prefijo del nivel, como «avanzado/02-integraciones-apis» (ver_temario los lista).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / slug / description
      Previous value: -"Slug de la lección, p. ej. 05-herramientas o avanzado/02-integraciones-apis (ver_temario los lista)."New value: +"Slug de la lección, hasta 80 caracteres: «05-herramientas» en el Básico o con el prefijo del nivel, como «avanzado/02-integraciones-apis» (ver_temario los lista)."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/openWorld, but the description adds real value: it discloses that the lesson body is NOT returned, that no account is needed, and that leer_leccion requires login plus level access. A minor gap remains on the exact shape of "cómo se accede", but the behavioral context is strong and consistent 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?

Front-loaded with purpose, then scope exclusion, then alternatives and error handling — logical and dense. It is three information-heavy sentences rather than padding, though slightly packed; every clause carries weight.

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 compensates by listing the returned fields, and it covers auth requirements, the alternative tool, and error recovery. An agent has everything needed to select and invoke it correctly.

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%; the schema alone documents the slug format, length limit and level-prefix examples. The description adds only a slight hint via the error case ("Si el slug no existe"), so the baseline of 3 applies since 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?

States a specific verb+resource ("Ficha pública de una lección") and enumerates exactly what it returns (resumen, objetivos, secciones, tiempo de lectura, cómo se accede, URL). It explicitly clarifies the negative scope ("No devuelve el cuerpo de la lección") and distinguishes itself from the sibling leer_leccion.

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?

Explicitly states when to use it ("para explicar qué enseña una lección sin necesidad de cuenta"), names the alternative for full content (leer_leccion, with its auth/level requirements), and gives fallback routing ("Si el slug no existe, llama a ver_temario"). Nothing is left to inference.

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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