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Glama
mcp-canvas-utem
by k0ngan

canvas_course_inventory

Counts modules, pages, assignments, files, announcements, and discussions in a Canvas course, then updates the course note with those totals; supports dry runs and course or term filters.

Instructions

Cuenta módulos, páginas, tareas, archivos, anuncios y discusiones, y actualiza la nota de curso con esos conteos.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "canvas_course_inventory"
  }
}

Input Schema

NameRequiredDescriptionDefault
termNo
dry_runNo
course_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the critical fact that this tool writes to the course grade, not just reads counts. However, it says nothing about whether overwriting an existing grade is destructive, what permissions are required, or what a 'dry run' would actually do, leaving the side-effect profile only half described.

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?

A single compact sentence with the read behavior front-loaded and the write side-effect as the trailing clause, so nothing is wasted. It is concise to a fault, since the brevity is what leaves the parameters and safety profile unexplained.

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?

For a tool that mutates a grade, with zero annotation coverage, zero schema description coverage, and no output schema, the definition should cover scope, dry_run semantics, and reversibility. It discloses the mutation but omits everything else an agent needs to call it safely, especially the meaning of dry_run.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across three parameters (term, dry_run, course_id), so the description must compensate and it does not: it never mentions scoping by term or course, and it completely omits dry_run, which is the safety valve for the grade-writing behavior. Only the notion of 'course' is loosely implied.

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 specific verbs (counts, updates) and enumerates the exact resources counted (modules, pages, assignments, files, announcements, discussions), so it is clearly an inventory-and-grade-write tool rather than a plain list tool like canvas_list_courses. It stops short of explicitly naming when a sibling such as canvas_sync_course or canvas_course_updates is the better choice.

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?

There is no statement of when to use this tool versus alternatives such as canvas_course_updates or canvas_sync_course, and no exclusions, prerequisites, or cost warnings. The only usage signal is implicit in the enumeration of counted resources.

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