Describe consumer group (with lag)

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds meaningful behavioral context by noting that lag is computed per-partition and total across topics, but it does not disclose what 'state' includes, whether offsets are committed or current, or what the response structure looks like.

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 one tightly written sentence that front-loads the action ('Describe') and packs the essential distinguishing detail ('compute per-partition and total lag') without waste. Every word contributes.

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 simple single-parameter, read-only tool with strong annotations, the description is mostly complete: it states the operation and the expected computed output. It lacks explicit mention of return shape, but no output schema exists and the core outcome is clear enough for an agent to call it successfully.

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% for the single required parameter, groupId, which is documented as 'Consumer group id'. The description adds no parameter-specific meaning beyond that, so the baseline score of 3 applies.

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 uses a specific verb ('Describe') with a clear resource ('a consumer group's state') and explicitly states the lag computation over partitions and topics. This clearly distinguishes it from siblings like list_consumer_groups (which lists groups) and topic_offsets (which likely returns offsets without group state).

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 when to use the tool—when inspecting a consumer group's state and lag—but it does not explicitly state how it differs from or when to prefer sibling tools like topic_offsets or list_consumer_groups. There is no exclusions or alternative guidance, so usage is inferred rather than explicit.

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