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list_course_resources

Read-only

Lists files and links in a Sakai course's Resources with type, size, and a shareable download link. Filter by folder to narrow long lists, then read files with get_resource.

Instructions

Files and links in a course's Resources, with resource_id, folder, type, size and a direct download_link to give the student (never a Sakai address, which needs a login). Use the folder input to narrow long lists, then get_resource to read a file.

Input Schema

NameRequiredDescriptionDefault
courseYesCourse code ('DCIT 301'), name, or site_id from list_my_courses
folderNoFolder path from a previous result, such as 'Slides'
refreshNoSkip the cache and ask Sakai again

Output Schema

NameRequiredDescriptionDefault
moreNoFiles not shown; narrow with the folder input
noteNo
folderNo
foldersYesAll folders in the course Resources
site_idYes
resourcesYes
course_codeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.1
    • addedOutput schema / $defs / Resource / properties / download_link
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Direct download link for the student; it works without logging in to Sakai",
      +  "title": "Download Link"
      +}
  2. First observedv0.2.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly and non-destructive, so safety is covered; the description adds the key behavioral guarantee that download_link is a student-usable direct link, never a Sakai address requiring login. It does not mention caching behavior for refresh, but that is documented in the schema.

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?

Two sentences, front-loaded with purpose, followed by the routing note. Every clause earns its place.

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?

Output schema exists, so return values needn't be detailed; the description nevertheless names the key fields and the download_link guarantee. Complete for a read-only list tool.

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%, so both course and folder are already documented in the schema. The description reinforces folder as a narrowing mechanism but adds no syntax or format detail beyond what the schema provides. 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 (list) and resource (course resources: files and links), enumerates returned fields, and distinguishes itself from get_resource, which reads a file. An agent can tell what it returns without opening the 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 names the folder input as the way to narrow long lists and routes the agent to get_resource for reading a file, giving both the when-to-use condition and the alternative. 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.