Canvas MCP Server

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool performs analysis and sends reminders, implying a write operation, but doesn't detail permissions needed, rate limits, side effects (e.g., data modification), or error handling. This is insufficient for a tool that likely involves data processing and messaging.

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 well-structured, with a clear purpose statement followed by parameter and return value sections. Every sentence adds value, and it's front-loaded with the main functionality. Minor improvements could include bullet points for readability, but it's efficient overall.

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 (involving analysis and messaging), no annotations, and an output schema (which covers return values), the description is partially complete. It outlines the workflow and parameters but lacks behavioral details like permissions or side effects. The output schema mitigates some gaps, but the description should do more for a multi-step operation.

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 description lists the two parameters (course_identifier and assignment_id) and their purposes, adding meaning beyond the schema's 0% coverage. However, it doesn't explain format constraints (e.g., valid ID ranges) or interactions between parameters. With two parameters and low schema coverage, this provides basic but incomplete semantic context.

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: 'analyze peer reviews and send targeted reminders.' It specifies the verb ('analyze' and 'send') and resource ('peer reviews'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'send_peer_review_reminders' or 'get_peer_review_followup_list', which could cause confusion about its unique scope.

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 mentions a 'complete workflow' but doesn't specify prerequisites, timing, or exclusions. Given sibling tools like 'send_peer_review_reminders' and 'get_peer_review_followup_list', the lack of differentiation leaves the agent without clear usage criteria.

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