explain_metric

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

No annotations are present, so the description carries the behavioral burden. It discloses the output nature (definition/methodology/caveats), the important constraint that it never returns a current figure, supported country values, and the stat_key dependency; it does not spell out read-only/no-side-effect or error behavior, but the core behavior is clear.

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 structure is front-loaded: usage rule, output scope, exclusions, then parameter provenance. However, the 'when to use' rule is repeated in the opening and again in the fourth sentence, so some trimming is possible.

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?

For a simple two-parameter explanation tool with an output schema, the description supplies the critical routing, scope, and stat_key provenance. No major invocation detail is 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%, so the description must compensate. It explains that stat_key comes from query_data(country=...) for the same country and lists the supported country values, covering both parameters, though it does not mention the default country or stat_key format.

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 states that the tool returns definition, methodology, and standing caveats for one metric, and explicitly says it never returns a current figure. It distinguishes itself from query_data and compare by routing numeric questions to those 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?

It explicitly says to use this when the question is about what a metric means or how it is measured, not for a figure, and names query_data/compare as the alternatives. It also states where stat_key comes from, giving the agent a clear invocation path.

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