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Eurostat — EU Youth Employment Rate by Education

eurostat2.employment.youth
Read-onlyIdempotent

Retrieve annual youth employment rate by educational attainment for EU/EEA countries from Eurostat (dataset: yth_empl_010, SDMX 2.1). Returns employment rate (% of age group) for youth aged 15–24 (default), 15–19, 15–29, 20–24, or 20–29, across all ISCED education levels combined. Country accepts ISO 3166-1 alpha-2 codes (DE, FR, ES, IT) or EU27_2020. Data covers 2005–present (with ~1 year lag). Useful for EU youth policy research, labour market analysis, and education-employment gap studies. Source: Eurostat LFS, CC BY 4.0, no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryYesEurostat geo code: ISO 3166-1 alpha-2 country (e.g. DE, FR, ES) or EU aggregate (EU27_2020)
age_groupNoYouth age group: Y15-24=15 to 24 years (default), Y15-19=15 to 19 years, Y15-29=15 to 29 years, Y20-24=20 to 24 years, Y20-29=20 to 29 years
since_yearNoFirst year to include (integer, e.g. 2010). Defaults to 2005.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, so the description need not repeat those. It adds valuable behavioral details: returns percentage values, defaults to Y15-24 age group, combines all ISCED education levels, covers 2005–present with a lag, and states 'no auth required'. This enriches the agent's understanding beyond structured fields and aligns with the annotations.

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?

Description is compact and front-loaded: first sentence states purpose, resource, and scope; second covers outputs; third provides parameter hints; fourth gives usage context; last covers source/licensing. Each sentence earns its place, though it could be slightly trimmed (e.g., the 'Useful for' sentence is somewhat generic). Overall efficient.

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 read-only data retrieval tool with an output schema present, the description is complete: it specifies data format (percentage), range, geography, no auth, and data source. It does not explicitly mention pagination or dataset size, but these are handled implicitly by the output schema and the tool's simple parameter set. Minor omissions (e.g., whether data is annual only) are hinted by 'annual youth employment rate'.

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

Parameters4/5

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

Schema coverage is 100%, so parameters are well-documented (country, age_group enum with per-value descriptions, since_year with default). The description adds context not fully captured in schema: it clarifies education levels are combined across all ISCED, provides example country codes (DE, FR, ES, IT) and the EU27_2020 aggregate, and restates the default age group and since_year default. This extra guidance helps correct parameter selection.

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?

Description states a specific verb ('Retrieve'), resource ('annual youth employment rate by educational attainment'), geographic scope ('EU/EEA countries'), and identifies the exact dataset (yth_empl_010, SDMX 2.1). It also specifies return units ('% of age group') and age groups, clearly distinguishing it from sibling Eurostat tools like eurostat2.demographics.fertility or eurostat2.energy.renewable.

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?

Provides clear context for when to use: 'Useful for EU youth policy research, labour market analysis, and education-employment gap studies.' It also includes data availability (2005–present, ~1 year lag) and no-auth requirement. However, it does not explicitly compare to alternatives or state when not to use this tool versus other unemployment indicators, which would push it to 5.

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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