list_topicsList Kafka topic names, filtering out those not in the allowlist. Optionally include internal topics starting with underscore.
List topic names. Topics outside the allowlist are filtered out.
| Name | Required | Description | Default |
|---|---|---|---|
| includeInternal | No | Include internal topics (starting with _) |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate read-only, idempotent, non-destructive behavior, so the description only needs to add extra context; the allowlist-filtering statement does that. It does not explain the allowlist semantics or how includeInternal interacts with it, so this is modest rather than thorough.
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 short sentences, front-loaded with the main action; no filler. 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?
A simple enumeration tool with one optional boolean and no output schema; returning names and the filter behavior is enough for an agent to call it. Additional details such as pagination or an allowlist definition would be helpful but are not essential for basic invocation.
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 single parameter includeInternal is fully described by the schema (including the '_' convention), and schema coverage is 100%. The description therefore adds little parameter-level value but does not need to.
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 topic names') and makes the filtering behavior explicit. This clearly separates it from descriptive/inspection siblings such as describe_topic and topic_offsets, which focus on details rather than enumeration.
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 phrase 'List topic names' establishes the obvious use case: when an agent needs an enumeration of available topics. It does not explicitly name alternatives or exclusions, but the context is clear enough for a read-only listing tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.