db_list_kafka_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 discloses the operation, the input, and the return type ('List of Kafka topics'), and the Kafka-only scope adds useful behavior context. It does not mention pagination, error cases, or whether the database must be pre-existing, but for a simple read operation this is minimally adequate.

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 compact and well-structured with separate Args and Returns sections. Every sentence carries information, with no fluff or repetition of the tool name.

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 one-parameter read-only list tool with an output schema available, the description covers the essential information: what it lists, the required parameter semantics, and the return type. It could add an example or mention behavior when the database_id is invalid, but nothing critical 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 input schema only says database_id is a string, while the description adds meaningful semantics: 'The Kafka database ID or label'. This helps the agent understand what value to supply and clarifies that labels are accepted, which is valuable 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?

States a specific verb and resource: 'List Kafka topics', with an explicit scope qualifier '(Kafka databases only)'. This clearly distinguishes it from generic database list tools like db_list_databases and from topic mutation siblings like db_create_kafka_topic.

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?

Provides clear context that this tool applies only to Kafka databases, which helps the agent decide when it is appropriate. It does not explicitly name alternatives or exclusions, but the scoping statement is sufficient for a simple read operation with no competing list-topics sibling.

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