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

Annotations already declare readOnlyHint=true, so the safe-read profile is established and the bar is lower. The description adds the return-content scope (which metric families are included) and the underlying endpoint, but says nothing about permissions, aggregation window, or whether values are per-course or cumulative.

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 compact clauses with zero waste: the metric summary is front-loaded and the endpoint reference trails as supporting detail. Nothing is repeated or padded.

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?

For a one-parameter read-only analytics tool with annotations covering safety, the description is nearly sufficient, and its metric enumeration partially substitutes for the absent output schema. Missing only framing details such as the reporting period or aggregation scope.

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?

Single required parameter with 100% schema description coverage — the schema already documents that course_id is the slug. The description adds no parameter-level detail beyond the schema, so the baseline 3 holds.

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+resource (course analytics) and enumerates the metric categories returned — students, learning units, average score, study time, social interactions, certificates — which visibly separates it from siblings like get_course_grades (per-student grades) or get_course. It does not name those alternatives, but the metric list makes the distinct purpose clear.

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?

No explicit when-to-use guidance, no conditions, and no routing to alternatives such as get_course_grades or get_user_course_progress. The metric list hints at the use case but the agent is left to infer when this tool is appropriate versus its siblings.

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