get_topic_etelatency

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

With no annotations and a minimal description, the tool does not disclose behavioral traits such as read-only nature, authentication requirements, or side effects. The description provides no additional context beyond the basic action.

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 extremely concise (7 words) and front-loaded with the action 'Get'. However, this brevity sacrifices necessary detail, making it less effective for agent selection.

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 has four parameters with no schema descriptions, the description should compensate but does not. The presence of an output schema partially mitigates the need for return value explanation, but parameter guidance is critically missing.

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%, yet the description does not explain the purpose of parameters like 'duration', 'from_time', or 'to_time'. The agent is left to infer their meaning without any guidance on formatting or semantics.

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', resource 'topic', and metric 'end-to-end latency', making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_topic_group_etelatency', which also deals with latency but at a group level.

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?

No guidance is provided on when to use this tool versus alternatives, or on the context for the optional time parameters (duration, from_time, to_time). An AI agent receives no direction on how to choose between similar tools.

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