Canvas LMS MCP Server

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 that it returns 'Dict with enrollment items including course IDs and grade data,' which gives some output context, but does not cover critical aspects like authentication needs, rate limits, error conditions, or whether it's a read-only operation. For a tool with zero annotation coverage, this is insufficient.

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 concise and front-loaded, with the main purpose stated clearly in the first sentence. The second sentence adds useful output information without redundancy. However, it could be slightly more structured by explicitly separating purpose and output details, but overall it is efficient with minimal waste.

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?

Given the tool's complexity (simple read operation with no parameters) and the lack of annotations and output schema, the description is partially complete. It explains what the tool does and the return format, but misses behavioral details like authentication or error handling. For a tool with no structured data support, it 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.

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

The input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description does not add parameter-specific information, which is appropriate here. Since there are no parameters, the baseline score is 4, as the description need not compensate for any gaps.

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's purpose: 'Get the current user's enrollments including grades.' It specifies the verb ('Get'), resource ('enrollments'), and scope ('current user's'), but does not explicitly differentiate it from sibling tools like 'list_courses' or 'list_assignments', which might also relate to user data in an educational context.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, such as how it differs from 'list_courses' or when grades might not be available. This lack of guidance could lead to confusion among similar sibling tools.

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