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 effectively describes the tool's behavior by specifying the data returned (offsets and lag) and a key feature (highlighting non-zero lag partitions). However, it does not cover aspects like rate limits, authentication needs, or error conditions, leaving some gaps for a tool that likely queries a monitoring system.

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, well-structured sentence that efficiently conveys the tool's purpose and key behavior without unnecessary words. It is front-loaded with the main action and includes essential details, making it highly concise and effective.

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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is reasonably complete. It covers what the tool does and a behavioral trait, but lacks details on output format, error handling, or dependencies. With no output schema, more information on return values would be beneficial, but it is sufficient for basic understanding.

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 has 100% description coverage, clearly documenting both parameters ('cluster_name' and 'group_id'). The description does not add any additional meaning or context beyond what the schema provides, such as format examples or constraints. Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

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 ('Get') and resource ('consumer lag for a specific consumer group'), with specific details about what data is retrieved ('per-partition offset, end offset, and lag') and a behavioral trait ('Highlights partitions with non-zero lag'). It distinguishes itself from siblings like 'kafka_list_consumer_groups' by focusing on detailed lag metrics rather than listing groups.

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 usage when needing detailed lag metrics for a specific consumer group, but does not explicitly state when to use this tool versus alternatives like 'kafka_list_consumer_groups' or 'kafka_describe_topic'. It provides context but lacks explicit guidance on exclusions or prerequisites.

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