list_topics

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

With no annotations, the description carries the full behavioral burden. It implies a read-only enumeration by saying 'Every logged uORB topic,' but it does not explicitly disclose read-only status, error behavior, or log requirements. It does state the returned fields, which adds some useful output context.

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 a single front-loaded sentence with no wasted words. It communicates the resource and the key return contents immediately.

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?

An output schema exists, so return values need not be fully explained, and the only parameter is documented in the schema. The description is minimally adequate but omits usage context relative to siblings, leaving selection guidance incomplete.

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?

Schema description coverage is 100%, so the single 'log' parameter is already fully documented in the schema. The description adds no parameter semantics beyond the schema, making the baseline of 3 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 names the resource ('logged uORB topic') and the returned metrics ('sample count, rate and field count'), which is specific enough to distinguish it from list_logs and topic_data. However, it does not explicitly name an alternative or exclude sibling tools, so it falls short of a 5.

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 description says what is returned but gives no explicit guidance on when to use list_topics versus siblings like list_logs, log_messages, or topic_data. There is no mention of prerequisites, appropriate workflows, or exclusions.

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