ilias_list_courses

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is fully covered. The description adds useful context beyond annotations: the data source is the ILIAS dashboard and the results include ref_ids and semester sections. It does not address scoping questions such as whether all enrollments are returned or how results are ordered, and an output schema exists to cover return values.

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?

A single short sentence with no filler, and the key qualifier (the user's courses and groups) is front-loaded. The sentence fragment lacks a verb, which costs a little at the margins but nothing is redundant.

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 read tool with full annotations and an output schema, the description is minimally sufficient: it says what list is returned and what fields matter. It stops short of explaining how the returned ref_ids relate to downstream tools or whether the list is filtered to active enrollments, which would have made it complete.

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 and the baseline of 4 applies. The mention of ref_ids and semester sections describes returned content rather than inputs, which is harmless and slightly helpful framing.

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 the specific resource ('the user's courses and groups from the ILIAS dashboard'), which is enough to distinguish it from siblings like ilias_list_assignments or ilias_list_news. It is a noun phrase with no verb, but the tool name supplies the 'list' action, so the overall purpose is clear without opening the schema.

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?

There is no explicit guidance on when to call this versus the many sibling list tools, nor any stated preconditions. A weak usage signal is implied by mentioning ref_ids (i.e. call this first to obtain identifiers other tools need), but the agent must infer that rather than being told.

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