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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds real behavioral context: annual World Bank-only sourcing, no live data/forecasts/regions, and the fallback of returning the latest year when no year is passed. The return-field list is partly redundant given an output schema exists, which keeps this from a 5.

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?

Three dense sentences, front-loaded with the usage trigger and clipped with the scope limitation. Every clause carries information; nothing is padding.

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?

An output schema exists, so the description does not need to spell out return values in depth, and it supplies the remaining essentials: source scope, year fallback, and what data is out of bounds. An agent has everything needed to call this correctly.

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 coverage is 100% and each parameter is already documented, including the indicator enum and the year default. The description restates the indicator list and country formats rather than adding syntax or resolution rules beyond the schema, 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?

States a specific verb and resource ('one official statistic for one country') and anchors it with two concrete user-phrasing examples. The singular 'one statistic for one country' scope immediately separates it from compare_countries and get_imf_forecast.

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 an explicit trigger ('Use this when the user asks for one official statistic for one country') and clear exclusions ('no live data, forecasts or regions'), which implicitly rules out the forecast sibling. It stops short of naming the alternative tools directly, so the routing is inferred rather than stated.

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