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Glama

Describe consumer group (with lag)

describe_consumer_group
Read-onlyIdempotent

Fetch a Kafka consumer group's state and compute per-partition and total lag across its topics.

Instructions

Describe a consumer group's state and compute per-partition and total lag across its topics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupIdYesConsumer group id

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.2
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds that lag is computed across topics, implying a heavier read, but says nothing about cost, latency, or what happens for a group with no active members – a 3 is appropriate given the structured data does most of the work.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One tight sentence, front-loaded with the primary action and followed by the secondary computation. Nothing wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with full annotation coverage and no output schema, the description is adequate but leaves two gaps an agent would care about: no routing guidance versus list_consumer_groups, and no indication of what the response contains now that the lag computation is the distinguishing feature.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with a single groupId parameter documented in the schema, so the schema carries the meaning. The description adds no format or scoping detail (e.g. whether groupId is cluster-qualified), so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (describe) and resource (consumer group), plus a second capability (compute per-partition and total lag). It is clearly distinct from list_consumer_groups by being single-group and lag-aware, though it never names that sibling to make the distinction explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance and no alternatives named. An agent cannot tell from the description whether to reach for this or list_consumer_groups/describe_topic for a given question; the lag mention implies a use case but does not state it.

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