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canvas_list_discussion_topics

Retrieve all discussion topics within a specific course using the Canvas MCP Server V2.0, enabling efficient management and review of course-related discussions.

Instructions

List all discussion topics in a course

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idYesID of the course

Implementation Reference

  • src/index.ts:521-529 (registration)
    Registers the canvas_list_discussion_topics tool including its name, description, and input schema that requires a course_id.
    name: "canvas_list_discussion_topics",
    description: "List all discussion topics in a course",
    inputSchema: {
      type: "object",
      properties: {
        course_id: { type: "number", description: "ID of the course" }
      },
      required: ["course_id"]
    }
  • Core handler function in CanvasClient that makes the API request to retrieve discussion topics for a given course, including related assignments.
    async listDiscussionTopics(courseId: number): Promise<CanvasDiscussionTopic[]> {
      const response = await this.client.get(`/courses/${courseId}/discussion_topics`, {
        params: {
          include: ['assignment']
        }
      });
      return response.data;
    }
  • TypeScript interface defining the structure of Canvas discussion topics returned by the tool.
    export interface CanvasDiscussionTopic {
      id: number;
      title: string;
      message: string;
      html_url: string;
      posted_at: string;
      assignment_id: number | null;
      assignment?: CanvasAssignment;
      discussion_type: string;
      require_initial_post: boolean;
      user_has_posted: boolean;
      discussion_subentry_count: number;
      read_state: 'read' | 'unread';
      unread_count: number;
    }
  • Handler for reading discussion topics as a resource (discussions://{course.id}), which calls the same underlying client method.
    content = await this.client.listDiscussionTopics(parseInt(id));
    break;
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 states the tool lists topics but does not mention any behavioral traits like pagination, rate limits, permissions required, or what the output format might be. For a list operation with zero annotation coverage, this is a significant gap in transparency.

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 a single, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose without unnecessary elaboration, earning a top score for brevity and clarity.

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?

Given the lack of annotations and output schema, the description is incomplete for a list tool. It does not cover behavioral aspects like pagination, sorting, or error handling, nor does it hint at the return format. For a tool with no structured support, the description should provide more context to be fully helpful.

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?

The input schema has 100% description coverage, with the 'course_id' parameter clearly documented. The description does not add any meaning beyond the schema, such as explaining where to find the course ID or its format. Given the high schema coverage, a baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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 action ('List') and resource ('all discussion topics in a course'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'canvas_get_discussion_topic' (which likely retrieves a single topic), leaving room for slight ambiguity in sibling distinction.

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, such as 'canvas_get_discussion_topic' for a single topic or other list tools for different resources. It lacks any context about prerequisites, exclusions, or typical use cases, offering minimal usage direction.

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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