list_topics

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

No annotations are provided, so the description carries full burden. It discloses the 'non-internal' filtering behavior and the fields returned (partition count, replication factor). This adds meaningfully beyond the empty schema, though it doesn't discuss potential latency or side-effect details beyond the read-only nature implied.

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 sentences with zero waste. The first sentence states the core function, the second provides placement guidance. Every word earns its place.

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-only list tool with an output schema, the description covers the filtering scope, return fields, and usage context. It's nearly complete; the only minor gap is not explicitly noting it's a read-only operation, though that's strongly implied.

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 has zero parameters, so there's no parameter documentation burden. The description adds value by describing the return content (partition count, replication factor), which compensates for the empty 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?

Clearly states it lists non-internal topics with partition count and replication factor. The verb+resource+scope is specific and distinguishes it from siblings like consumer_lag and partition_state which focus on different aspects of topic state.

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?

Explicitly advises to use this tool first if you don't already know a topic name, noting that every other tool needs one. This is clear, actionable guidance on when to invoke this tool versus alternatives.

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