EU Monthly Unemployment Rate

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

The description adds key behavioral context beyond annotations: it specifies the metric (percentage of active population, seasonally adjusted), the scope (one country per call), and the data source and licensing. The annotations already indicate read-only, idempotent, and open-world behavior, which are consistent.

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 sentence that packs essential information: what, when, scope, data source, and licensing. No unnecessary words.

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 the tool's simplicity (3 parameters, output schema present), the description adequately covers the data source, unit, seasonality, and scope. It provides sufficient context for an agent to use the tool 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?

The input schema has 100% description coverage, with clear parameter descriptions. The tool description adds little beyond listing geo code examples and aggregates, which is already present in the schema. Baseline 3 is appropriate as description does not significantly enhance parameter understanding.

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 states the tool provides the monthly unemployment rate for EU countries or aggregates, with specific data source (Eurostat dataset une_rt_m) and licensing. It distinguishes from sibling tools like finance.eurostat.gdp_growth, finance.eurostat.inflation, and finance.eurostat.population.

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?

The description implies usage for retrieving EU unemployment data but does not explicitly state when to use this tool versus alternatives (e.g., other Eurostat tools). There is no guidance on when not to use or prerequisite conditions.

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