Server metrics

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

No annotations are provided, so the description carries the burden. It does disclose that only non-zero metrics are returned and names example metric areas, which is useful. However, it does not describe the return format, units, or any operational constraints.

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, efficient sentence that front-loads the key behavior (non-zero metrics) and gives helpful examples. It is concise without being a vague tautology.

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 this is a simple zero-parameter metrics tool, the description is mostly sufficient, but the absence of an output schema means the agent still lacks concrete information about response shape. It covers what the tool does but not all an agent might need to interpret the result.

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 tool has zero parameters, so parameter semantics is not a real burden on the description. The baseline of 4 applies here; the description correctly focuses on what the tool returns rather than input details.

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 identifies the tool as returning server metrics from system.metrics and even highlights the non-zero filtering and metric families. It does not use an explicit verb, but it is specific enough to distinguish from the database-/table-focused siblings.

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?

There is no guidance on when to prefer server_metrics versus alternatives like cluster_info or running_queries. The usage context is only implied by the name and metric examples, not explicitly stated.

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