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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context: the endpoint returns only cohorts with a common schedule, excludes students without a cohort, and distinguishes progress as a separate resource. For a zero-parameter read-only tool this is sufficient.

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 compact and front-loaded with the core output fields, followed by a definition and boundary/edge-case routing. Every sentence earns its place with no filler.

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 simple, parameterless, read-only list endpoint with no output schema, the description fully covers what is returned, the concept of a cohort, exclusions, and pointers to related tools. Nothing needed for correct invocation is missing.

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 tool has zero parameters and 100% schema coverage (empty schema), so there is nothing for the description to clarify about arguments. The baseline for zero-parameter tools 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?

The description identifies the resource (cohorts/потоки) and the fields returned (course, start/end dates, enrollment count), and it distinguishes this tool from cohort_progress and stuck_students by scope. However, it lacks an explicit verb such as 'list' or 'returns', relying on the tool name and context to convey the action.

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 explicitly states that students outside cohorts are not included and directs the agent to stuck_students without cohort_id for that case, while also pointing to cohort_progress for progress data. This provides clear when-to-use and when-not-to-use guidance with named alternatives.

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