List Kafka cluster topics by name pattern while excluding internal system topics by default.
列出 Kafka 集群中的主题清单（支持按名称模式过滤并默认排除内部系统主题）
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | No | ||
| connection | No | ||
| include_internal | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.3.1Input schema / properties / connectionAdded value: +{
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "title": "Connection"
+}v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose two real behaviors beyond the schema: name-pattern filtering is supported and internal system topics are excluded by default, which adds value. However it says nothing about the connection parameter, auth/permissions, or any operational constraints.
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, and the filtering/scope caveat is bundled inline rather than buried. Efficient, though it is arguably under-specified rather than optimally concise.
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?
An output schema exists so return values need not be explained, but with no annotations and 0% schema coverage the description should do more. The connection parameter is never explained and there is no permission or scope context, leaving the agent guessing on a 3-parameter tool.
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?
Schema description coverage is 0%, so the description must compensate. It only loosely gestures at two of the three parameters (pattern filtering, internal exclusion) without specifying pattern syntax (glob? regex?) and completely omits the connection parameter, leaving a third of the surface undocumented.
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 (列出/list) and resource (Kafka 集群中的主题/topics in a Kafka cluster), which cleanly distinguishes it from the single-topic sibling kafka_describe_topic. It does not explicitly name or contrast with any sibling, so it falls just short of a 5.
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 obvious use case (enumerate topics) but offers no when-to-use versus kafka_describe_topic, no prerequisites, and no exclusions. The only usage-adjacent detail is the default internal-topic exclusion, which is a behavior, not routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.