My Courses

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds context by specifying the exact data returned (course code, term, role) and its role in resolving course IDs for other tools. It does not contradict the annotations and provides useful scoping beyond the structured metadata.

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 two sentences that are both information-dense and purposeful. The first sentence states the action and output; the second provides the key usage context. There is no redundancy, filler, or unnecessary detail, making it highly concise for an AI agent.

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 low complexity (one optional parameter), full schema coverage, provided annotations, and an output schema, the description fully covers the necessary context. It explains what the tool does, what is returned, and the practical use case (resolving course_id), leaving no critical gaps.

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?

Schema description coverage is 100% because the single 'state' parameter has a clear description. The tool description does not add further parameter-level detail, but the schema already fully documents the parameter. Baseline of 3 is appropriate since the description does not need to compensate.

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 uses a specific verb ('List') and resource ('user's Canvas courses'), defines the returned fields (course code, term, role), and clearly distinguishes from sibling tools by stating its role in resolving course name/code to course_id. This is not a tautology and fully differentiates the tool.

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 explicitly states when to use the tool: 'Use this to resolve a course name or code to the course_id that other tools require.' This gives clear context and a primary use case. However, it does not mention when not to use or explicitly name alternative tools, so it falls short of the highest bar.

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