List Course Appointments

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the description only needs to add context. It adds the pass-through behavior ('unchanged') and the layerId provenance caveat, but does not disclose pagination shape or how direction affects results.

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?

Two sentences with no filler; the core operation is stated first and the critical parameter caveat is second. Every sentence earns its place.

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?

The description is adequate for the required parameter but not fully complete: no output schema exists, and pagination behavior plus direction semantics are not explained. The layerId warning is valuable, yet an agent still lacks guidance on how limit, cursor, and direction should be used.

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?

With 0% schema description coverage, the description must carry parameter meaning. It does clarify layerId's required source, but limit, cursor, and direction are left entirely to their schema names/defaults, which is only partial compensation.

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 names a specific action and resource: 'Return one course's appointment page unchanged.' It scopes to a single course and warns about layerId provenance, which helps distinguish it from learning-unit tools, though it does not explicitly contrast it with list_student_appointments.

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?

It gives a clear precondition: supply layerId from enrolled or bookable course data, not the learning-unit course id. However, it does not state when to choose this tool over list_student_appointments or list_bookable_courses, leaving the selection inference to the agent.

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