ntulearn_list_courses

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds a genuinely useful behavioral detail beyond annotations: the default result set silently excludes unavailable courses, which an agent must know to avoid misreporting a user's enrollments.

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?

Three short sentences, front-loaded with what is listed and scoped, followed by the default behavior and the override, then pagination. No filler and every clause carries information.

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?

With annotations covering safety, a full output schema, and 100% schema description coverage, the definition supplies the one thing structured data cannot: the default filtering semantics and the override flag. Return shape and pagination mechanics are adequately covered elsewhere, leaving only minor 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%, so all four parameters are already fully documented in the schema, including limit bounds, offset/nextOffset usage, the response_format enum, and the include_disabled meaning. The description's mention of include_disabled and limit/offset restates what the schema already carries, so the baseline 3 applies.

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?

States a specific verb ('List') plus resource ('courses the current user is enrolled in') and names the platform, giving the exact scope. This is clearly distinguishable from sibling tools that act on course contents, assignments, announcements, or gradebooks rather than the enrollment list itself.

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 default-filter behavior ('returns only active/available courses') and the opt-in to include disabled ones imply when to use the flag, but no alternative tool is named and no explicit when/when-not guidance is given. Usage context is inferable rather than stated.

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