update_consumer_group_topic_partition_offset

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 states the action ('Update the offset') but fails to mention critical details like required permissions, whether the operation is idempotent, potential side effects (e.g., impact on consumer group state), or error handling. This leaves significant gaps for an AI agent to understand the tool's behavior beyond basic functionality.

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 structured with a clear purpose statement followed by 'Args' and 'Returns' sections, making it easy to parse. It avoids unnecessary verbosity, though the parameter explanations are minimal. Every sentence serves a purpose, but the lack of deeper context slightly reduces efficiency.

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 complexity of a 5-parameter mutation tool with no annotations, the description is moderately complete: it covers the basic operation and parameters. However, it lacks details on behavioral traits, usage context, and output specifics, despite having an output schema. For a tool that modifies consumer group offsets, more guidance on implications and alternatives would enhance completeness.

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 by explaining parameters. It lists all five parameters with brief labels (e.g., 'environment: The environment name'), adding minimal semantic context beyond the schema's titles. However, it does not clarify parameter relationships, valid ranges (e.g., for 'offset'), or examples, providing only basic definitions that partially address the coverage gap.

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 ('Update') and resource ('offset for a topic-partition for a given group'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'update_consumer_group_offsets' or 'delete_consumer_group_topic_partition_offset', which handle similar resources but with different operations.

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 provides no guidance on when to use this tool versus alternatives, such as 'update_consumer_group_offsets' (which might update multiple offsets) or 'delete_consumer_group_topic_partition_offset' (which removes an offset). It lacks context on prerequisites, error conditions, or typical use cases, offering only basic parameter information.

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