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ahnopologetic

Canvas LMS MCP Server

list_quizzes

Fetch quizzes for a Canvas course by course ID. Optionally include additional data and paginate results with page and items per page parameters.

Instructions

List quizzes for a course.

Args: course_id: Course ID include: Optional list of additional data to include page: Page number (1-indexed) items_per_page: Number of items per page

Returns: PaginatedResponse containing quizzes

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idYes
includeNo
pageNo
items_per_pageNo
Behavior3/5

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

Without annotations, the description carries full burden. It discloses that the tool returns a PaginatedResponse and uses pagination parameters, which is helpful. However, it does not explicitly state that the operation is read-only, nor mention error handling, rate limits, or auth requirements. The provided details are moderate.

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?

The description is very concise: two sentences for purpose and a bullet-style list of parameters and return info. No wasted words, and critical information is front-loaded. It is easy to scan and understand quickly.

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

Completeness3/5

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

Given 4 parameters, no output schema, and no annotations, the description covers the basic purpose, parameters, and return type. It is incomplete in lacking usage context, error conditions, and details on the 'include' parameter. More depth would improve completeness for an AI agent.

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 0%, so the description must add meaning. It lists each parameter with a brief explanation (e.g., 'course_id: Course ID'), which adds some semantics beyond the schema titles. However, explanations are minimal; for instance, 'include' is described as 'Optional list of additional data to include' without specifying available options.

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?

The description clearly states 'List quizzes for a course.' This is a specific verb+resource combination that matches the tool name and distinguishes it from sibling tools like list_assignments or get_quiz. No ambiguity.

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 provided on when to use this tool over alternatives, such as get_quiz for a single quiz or other list tools. The description implies a course_id is needed but does not specify when not to use it or mention any prerequisites beyond the required parameter.

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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