list_course_modulesList all modules in a Canvas course, optionally including module items, to get a structured view of course content and locate materials.
List modules and optionally module items in one Canvas course.
| Name | Required | Description | Default |
|---|---|---|---|
| course_id | Yes | Canvas course ID | |
| include_items | No | Fetch module items for each module |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure. It only says 'list' without mentioning pagination, response format, error behavior, or any side effects. For a read operation it is minimal, but it does not reveal potential limitations like number of modules returned or handling of invalid course IDs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the primary action and includes the optional enhancement. Every word is necessary; there is no filler. This is an example of concise, effective communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description is incomplete. It does not describe the return value structure (e.g., an array of modules), pagination, or any access requirements. An agent would not know what to expect from the call or how to handle large course structures.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage of both parameters with descriptions. The description adds little beyond the schema: it mentions 'optionally module items' which maps to include_items, but does not provide additional semantics like default behavior or format. Since schema coverage is high, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists modules and optionally module items for a single Canvas course. It uses a specific verb and resource, but does not explicitly distinguish it from sibling tools like get_course_bundle or list_course_assignments. The scope 'in one Canvas course' narrows it, but no alternative is mentioned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical use cases, or when to choose a different tool like get_course_bundle. The description simply states what it does, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.