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UK Data: Eurostat EU statistics

eu_unemployment_rate

Read-onlyIdempotent

Monthly unemployment rate (seasonally adjusted, % of the labour force aged 15-74) for one European country or the EU / euro area, optionally for men or women only. Answers "what is unemployment in Spain" for job seekers, analysts and reporters. Source: Eurostat dataset une_rt_m (ILO definition, so it can differ from national claimant counts). The newest month is sometimes not yet published for every country. (cost: 1 credit)

Input Schema

NameRequiredDescriptionDefault
nNointeger, optional, most recent months, 1-100, default 12
geoNostring, required, 2-letter Eurostat country code (DE, FR, ES, IT, NL, PL, EL = Greece) or country name; EU27_2020, EA (euro area), EA21, EA20 also accepted. EU, EFTA and EU candidate countries only (no UK)
sexNostring, optional: total (default), male or female (T, M, F)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

The annotations already establish that this is a safe, read-only, idempotent, non-destructive lookup with open-world coverage. The description adds real context beyond that: the 1-credit cost, the fact that the newest month may be unpublished for some countries, and the ILO definition caveat. Still, it says nothing about the shape or ordering of the returned series, which matters for a time-series tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is compact and front-loaded: measure, then unit, then geography, then audience, then caveats, then cost. Every sentence carries useful information, and the definition is slightly dense but never padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-parameter statistical lookup with no output schema, the definition covers units, coverage, source, definition caveat, publication lag and cost, which is enough for correct invocation. The one gap is that it never describes the shape of the response series (for example, date/value pairs), though this is minor for a simple read-only tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all three parameters (n, geo, sex) are already documented in the schema and the baseline is 3. The description adds only light framing: it clarifies that only one country or aggregate is covered per call, and that the sex filter is optional.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific measure (monthly, seasonally adjusted unemployment rate), a unit (% of labour force aged 15-74), a geography (one European country, EU, or euro area) and its source dataset (Eurostat une_rt_m). The explicit age band 15-74 implicitly distinguishes it from the sibling tool eu_youth_unemployment_rate, so the agent can choose between them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It anchors usage with a concrete example question ("what is unemployment in Spain") and a target audience, and it explains the ILO-vs-national-claimant distinction, which tells the agent when this data may not match national sources. What it does not do is explicitly route to the sibling eu_youth_unemployment_rate, or say when not to use this tool.

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

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