Skip to main content
Glama

s21_get_course_files

Retrieves all files, readings, and documents for a course, using a fallback method when the files tab is blocked or unavailable.

Instructions

Lista todos los archivos, lecturas y documentos disponibles en una materia, con soporte de fallback si la pestaña de archivos está bloqueada.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idYesID de la materia en Canvas.

Schema Changelog

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

  1. First observedv1.0.1

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the disclosure burden and does reveal that the tool has fallback behavior when the files tab is blocked. However, it does not clarify what the fallback returns, whether authentication is needed, or what happens when there are no files.

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

Conciseness5/5

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

A single, front-loaded sentence that states the core functionality and the notable fallback behavior in compact form. No filler or redundant wording.

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

Completeness4/5

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

For a one-parameter read-only listing tool, the description is largely complete: it names the inputs implicitly via course context, the output category (files/readings/documents), and a fallback path. It could be more explicit about output shape and fallback details, but it is sufficient for basic invocation.

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%: course_id is already documented as the Canvas course ID. The description adds only the contextual notion of 'una materia' and no format, bounds, or examples, so it earns the baseline score.

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 names a concrete action ('Lista') and a clear resource ('archivos, lecturas y documentos disponibles en una materia'), so an agent can tell what the tool retrieves. It does not explicitly contrast itself with overlapping siblings like s21_get_reading or s21_search_readings, so it stops short of full differentiation.

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 mention of fallback when the files tab is blocked gives some contextual trigger, but there is no explicit when-to-use versus s21_get_reading, s21_get_modules, or other course-content tools. Usage is implied rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/omniboyOK/siglo21-canvas-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server