list_all_courses

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

Annotations already declare readOnlyHint, destructiveHint=false, and openWorldHint, so the safety profile is covered. The description adds real behavioral context beyond that: results include archived courses, meaning the output can contain stale or inactive enrollments, which matters for downstream reasoning. It says nothing about result volume or ordering, though the output schema covers return shape.

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 short sentences with zero filler: the scope statement comes first, followed immediately by the decision rule for using it. Every clause earns its place and nothing is repeated from the schema or annotations.

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 zero-parameter list tool with an output schema and full annotation coverage, the description supplies what structured fields cannot: the active-plus-archived scope and the selection rule. The remaining gap is routing to list_active_courses and list_archived_courses, which an agent must infer from their names alone.

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 takes zero parameters, so there is nothing for the description to disambiguate beyond what the empty schema already states; baseline for a no-parameter tool is 4. The description correctly implies no filtering is possible, which is the one semantic point worth conveying.

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 verb ('List') and resource ('the full enrollment history'), and the phrase 'active plus archived courses' makes the scope precise. It does not name the obvious siblings list_active_courses and list_archived_courses, so differentiation is left to inference rather than stated.

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 concrete when-to-use condition: 'when you need to find a course across semesters without knowing whether it is currently active.' That effectively implies the narrower siblings are for the cases where you do know, but the alternatives are never named or explicitly excluded.

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