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ahnopologetic

Canvas LMS MCP Server

list_discussions

Retrieve and display discussion topics for a Canvas LMS course using pagination parameters to manage content viewing.

Instructions

List discussion topics for a course.

Args: course_id: Course ID page: Page number (1-indexed) items_per_page: Number of items per page

Returns: PaginatedResponse containing discussion topics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idYes
pageNo
items_per_pageNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions pagination and returns a 'PaginatedResponse', which adds some context, but it fails to describe critical behaviors such as authentication requirements, rate limits, error handling, or what specific data the response includes. This is inadequate for a tool with no annotation coverage.

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 front-loaded with the core purpose, followed by structured sections for arguments and returns. It is concise with no wasted sentences, though the formatting as a single block of text slightly reduces readability compared to bullet points or separate lines.

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 the tool's moderate complexity (3 parameters, no annotations, no output schema), the description covers the basic purpose and parameters but lacks details on behavioral traits, output structure beyond 'PaginatedResponse', and usage context. It is minimally adequate but has clear gaps that could hinder effective tool selection and invocation.

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

Parameters4/5

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

The description provides semantic meaning for all three parameters ('course_id', 'page', 'items_per_page'), explaining their roles beyond the basic schema. Since schema description coverage is 0%, this compensation is necessary and well-executed, though it could be more detailed (e.g., format for 'course_id' or constraints for 'items_per_page').

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 clearly states the verb ('List') and resource ('discussion topics for a course'), making the purpose immediately understandable. However, it does not explicitly differentiate this tool from sibling tools like 'list_announcements' or 'get_discussion_view', which would be needed for a score of 5.

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?

The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't mention when to choose 'list_discussions' over 'get_discussion_view' or other list tools, nor does it specify prerequisites or exclusions. This leaves the agent without contextual usage instructions.

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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