list_topics

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the 'active' scoping detail, which is useful, but it does not mention ordering, pagination, or the exact shape of returned topics.

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, front-loaded sentence contains the core action, the resource, and the active-topic filter. There is no redundancy or 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, read-only, single-parameter tool, the description plus schema and annotations are mostly adequate. It could be more complete by explicitly noting what fields are returned for each topic, but nothing needed to safely invoke the tool 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 schema covers 100% of the parameter and already describes study_id as returned by list_studies or create_study, and warns it is never a user id. The description adds little beyond the word 'study,' but the schema is sufficient, so the baseline of 3 is appropriate.

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 uses a specific verb ('Return') plus a clear resource and scope: 'active topics within a study.' This immediately distinguishes it from siblings like list_studies (studies, not topics) and list_subtopics (subtopics, not topics).

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?

The phrase 'within a study' implies the tool is for study-scoped topic listing, and the 'active' filter further narrows intent. However, there is no explicit statement about when to prefer this tool over list_subtopics or get_due_subtopics, nor any when-not-to-use guidance.

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