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Leer una lección

leer_leccion
Read-onlyIdempotent

Texto completo de una lección del curso, en Markdown, si el alumno tiene acceso (la 01 y el Básico con su cuenta; Avanzado y Experto si los ha comprado). Si no tiene acceso, devuelve la ficha pública y cómo conseguirlo. Necesita iniciar sesión. Úsala para estudiar o explicar una lección concreta con su texto; para saber de qué trata sin cuenta basta ver_leccion. Máximo 60 lecciones al día por alumno desde el servidor MCP; en la web no hay límite.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesSlug de la lección, hasta 80 caracteres: «03-ciclo-vida» 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. 03-ciclo-vida o avanzado/02-integraciones-apis (ver_temario los lista)."New value: +"Slug de la lección, hasta 80 caracteres: «03-ciclo-vida» en el Básico o con el prefijo del nivel, como «avanzado/02-integraciones-apis» (ver_temario los lista)."
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations: it discloses the access model (lesson 01 and Básico with an account; Avanzado/Experto only if purchased), the login requirement, the fallback behavior when access is denied (returns the public ficha and how to obtain it), and a concrete rate limit (60 lessons/day per student on MCP, unlimited on the web). This is exactly the kind of context 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.

Conciseness4/5

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

Front-loaded with the purpose, then access, then usage, then limits, with no filler sentences. It is dense and information-rich; slightly long for a single-parameter read tool, which keeps it just short of a 5.

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?

No output schema exists and there is one documented parameter, yet the description fully covers what the agent needs: what is returned, the access prerequisites, the denial fallback, and the rate ceiling. Nothing material is missing.

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% and there is a single well-documented `slug` parameter, so the schema already does the heavy lifting. The description adds only an indirect pointer ('ver_temario los lista') to where slugs come from, which is marginal added value. Baseline 3 is appropriate.

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 and resource: returns the FULL text of a course lesson in Markdown. It distinguishes itself from the similarly named sibling ver_leccion (public preview) by scoping the full-text/access-gated behavior, so an agent can pick the right tool without opening either schema.

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 tells when to use it ('para estudiar o explicar una lección concreta con su texto') and names the alternative for the no-account case ('para saber de qué trata sin cuenta basta ver_leccion'). The routing condition is unambiguous.

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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