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

With readOnlyHint/destructiveHint already covering the safety profile, the description adds real context: caveats define when the metric cannot be trusted, and broken_reason explains when a formula cannot be measured at all (e.g. a period column that does not parse as dates). It does not describe return format beyond these fields, but that is largely implied.

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?

Front-loads what the tool returns, then explains the caveats and broken_reason in two tight sentences. Dense but every clause carries semantics; the final parenthetical example is slightly long but illustrative.

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?

No output schema exists, so the description appropriately characterizes the returned content (formula, grounding, caveats, broken_reason) and flags the trust caveat. Missing only explicit sibling routing and any note on error behavior when a name is unknown.

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?

There is a single parameter and schema coverage is 100%; the schema already states 'Metric name from list_metrics'. The description adds no syntax, format, or validation guidance for the name, so baseline 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?

Names a specific verb (get) and resource (one metric) and enumerates exactly what the payload contains: formula in map terms, object.field grounding, and caveats. It is clearly distinct from list_metrics, which only enumerates names.

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?

Gives a clear trigger for use — read the caveats before computing or citing the number — and the parameter description routes discovery through list_metrics. It does not explicitly name list_metrics as the alternative in the main description or state when not to call it, so it stops short of full when/when-not guidance.

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