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

With no annotations, the description carries the behavioral burden and does well: it discloses that the tool returns definitions, methodology, and standing caveats for one stat and never returns a current figure. It also states the `stat_key` provenance constraint, though it does not discuss error behavior or limits.

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 front-loaded and appropriately sized, with the core distinction stated in the first line. It repeats the what-means/how-measured guidance and the `query_data` alternative, which is useful but slightly redundant.

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 an output schema exists, the description need not explain return values, and it still fully covers the nature of the response, the exclusion of current figures, and the prerequisite for `stat_key`. Nothing essential for correct invocation 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 identifies permitted country values ('ireland' or 'united-kingdom'), explains that `stat_key` comes from `query_data(country=...)`, and enforces that both must use the SAME country; it does not document the schema default, which keeps it from a 5.

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 a specific resource and purpose: definition, methodology, and standing caveats for ONE metric. It explicitly distinguishes this from getting a figure via `query_data` and from area comparisons via `compare`, so an agent can choose it without opening the schema.

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 gives explicit when-to-use and when-not-to-use guidance: use for meaning/methodology questions, not for a specific area's current value. It names the alternatives (`query_data`, `compare`) and the condition that selects them.

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