Cluster info

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

Annotations already declare the operation read-only, idempotent, open-world, and non-destructive. The description adds value by specifying the output scope (brokers, controller, cluster id), which is especially helpful given there is no output schema. No contradiction with annotations.

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 with no filler. Every word earns its place, and the colon-delimited list makes the scope immediately scannable.

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 tool, this is complete: annotations cover the safety profile, and the description states the expected return scope. No output schema exists, but the enumerated components give the agent a clear expectation.

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 the description has no parameter semantics to add. The baseline of 4 for no-parameter tools applies, and the description's component list effectively clarifies what the call returns.

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 ('Describe') and resource ('Kafka cluster'), and enumerates the exact components covered ('brokers, controller, and cluster id'). This clearly distinguishes it from sibling tools focused on topics, consumer groups, and offsets.

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 implies the use case by naming the cluster-level resource, but it does not explicitly state when to use this tool over siblings or mention alternatives for topic/group operations. Guidance is left to inference.

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