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s21_get_reading

Retrieve a specific reading or activity from a Canvas course by providing module and reading numbers, with optional automatic PDF text extraction.

Instructions

Busca y resuelve automáticamente una lectura o actividad específica por Módulo y Número de Lectura, con opción de extraer el texto del PDF directamente.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idYesID de la materia en Canvas.
auto_read_pdfNoSi es true (por defecto), descarga y extrae el texto del PDF automáticamente.
module_numberYesNúmero de módulo (1, 2, 3 o 4).
reading_numberYesNúmero de lectura o actividad (1, 2, 3 o 4).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals an automatic resolution action ('resuelve automáticamente') and optional PDF extraction, but does not explain what 'resuelve' entails, whether it modifies state, requires permissions, or what side effects occur. This ambiguity is significant for a tool whose name suggests a simple read.

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 a single sentence that front-loads the main purpose and then adds the optional capability. It contains no filler, but the ambiguity of 'resuelve' costs it a perfect score because the sentence could have been more explicit without losing conciseness.

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?

Despite full parameter documentation in the schema, the description omits what the tool returns or what 'resuelve automáticamente' actually does. There is no output schema and no annotations, so the description is the only source for expected results and side effects. This is insufficient for a tool with potential auto-resolution behavior.

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%, so the schema already documents all parameter meanings clearly. The description adds only contextual mapping between 'Módulo y Número de Lectura' and the module_number/reading_number fields, plus a hint that auto_read_pdf controls PDF extraction. This is baseline value, not additional semantic depth.

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?

The description states a clear action ('Busca y resuelve') on a specific resource ('una lectura o actividad específica') identified by module and reading number, and mentions the optional PDF text extraction. It distinguishes itself from broad search tools like s21_search_readings by emphasizing 'específica' and the exact keys, though the verb 'resuelve' is somewhat ambiguous about what actually happens.

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

Usage Guidelines2/5

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

No guidance is given on when to prefer this tool over alternatives such as s21_search_readings or s21_read_pdf_content. There are no conditions, exclusions, or explicit comparisons to sibling tools, leaving the agent to infer usage entirely from the description.

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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