list_topics

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

No annotations are provided, so the description fully carries the burden of transparency. It explicitly states 'Takes no arguments' and describes the return format with an example, which is helpful for an AI. However, it does not mention side effects, rate limits, or access restrictions; a slight gap relative to a perfect score.

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?

Three short sentences, no wasted words. Each sentence contributes: the first explains the action, the second clarifies arguments and output, the third provides usage guidance. Perfectly front-loaded with the key information.

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?

Given the tool is a simple, parameter-less discovery tool with a nested output schema and the description already includes an example of the return format, nothing is missing. The context signals confirm zero parameters and 100% schema coverage, so the description is fully complete for an AI agent.

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 input schema has zero parameters and 100% description coverage (none needed), so baseline is 4. The description adds no parameter semantics (since none exist), but this is correct because there is nothing to add beyond the schema.

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 ('list') and resource ('all ROS topics') while distinguishing from sibling tools (e.g., list_nodes) by specifying the output includes message types. This fully clarifies the tool's purpose.

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 states when to use this tool ('Call this first to discover... before subscribing or publishing'), providing clear context. It does not explicitly exclude alternatives, but the guidance is strong enough for an AI to understand the primary use case.

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