byok-observability-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates this is a read operation ('List') and specifies what data is returned. However, it doesn't mention important behavioral aspects like whether this requires authentication, rate limits, error conditions, or pagination behavior beyond what's in the schema. The description adds value by specifying the return data format but leaves gaps in operational context.

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 a single, efficient sentence that contains no wasted words. It front-loads the core purpose and includes all necessary information about what data is returned. Every element of the description serves a clear purpose in helping an agent understand what the tool does.

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 read-only listing tool with no annotations and no output schema, the description provides good coverage of what the tool does and what data it returns. It specifies the exact metrics included in the listing, which is valuable context. However, without annotations or output schema, it could benefit from more behavioral context about authentication, error handling, or response format details. The description is mostly complete but has minor gaps given the tool's complexity.

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 100%, so the schema already fully documents all three parameters. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. It mentions the resource being operated on (topics) which aligns with the cluster_name parameter, but provides no additional semantic context about parameters. Baseline 3 is appropriate when the schema does all the parameter documentation work.

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 clearly states the verb ('List') and resource ('topics in a Kafka cluster') with specific details about what information is included ('partition count, replication factor, and under-replicated partition count'). It distinguishes from siblings like kafka_describe_topic (which likely provides detailed topic metadata) and kafka_list_clusters (which lists clusters rather than topics).

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 doesn't explicitly state when NOT to use this tool, but it provides clear context for usage (listing topics with specific metrics). The input schema's description for cluster_name references kafka_list_clusters as an alternative for discovering available clusters, giving some guidance on prerequisites. However, it lacks explicit comparisons with other topic-related tools like kafka_describe_topic.

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