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reference-data

by dev.euroref

check_minimum_wage

PAID ($0.05). Compliance verdict: is a salary at, above or below the country's statutory minimum wage? Returns verdict, margin, the statutory floor and the legal instrument it rests on. Honest statuses when no enforceable floor exists or the period doesn't match the floor's period (cross-period conversion is never guessed). Pass api_key if you have one; otherwise the response explains how to pay via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYesWage to check, in the country's own currency
periodYesPeriod the amount covers — must match the statutory floor's period
api_keyNoAPI key (bypasses x402; metered for invoicing)
countryYesISO country code

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description fully discloses behavioral traits: it's a paid tool ($0.05), does not guess cross-period conversions, and returns honest statuses for edge cases (no floor, period mismatch). This is above average for a tool without annotations.

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

Conciseness5/5

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

The description is three sentences, front-loaded with core purpose, covering behavior and edge cases without superfluous text. Every sentence adds value.

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

Completeness5/5

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

Despite no output schema, the description enumerates return fields (verdict, margin, floor, legal instrument) and covers edge cases (missing floor, period mismatch). The tool's complexity is moderate and the description is sufficient for an agent to use effectively.

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 coverage is 100%, so baseline is 3. The description adds minor context (e.g., api_key bypasses x402) but does not significantly enhance understanding beyond the schema's own descriptions.

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 clearly states the tool checks if a salary meets the country's statutory minimum wage, with a specific verb 'check' and resource 'minimum wage'. It distinguishes from sibling tools (e.g., compute_income_tax, compute_vat) which handle different compliance calculations.

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

Usage Guidelines3/5

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

The description provides context about period matching and honest handling of missing floors, but does not explicitly state when to use this tool over siblings or specify prerequisites/exclusions.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct operation: minimum wage, income tax, VAT, working days, holidays, series data, and settlement dates. No overlap in purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (e.g., check_minimum_wage, compute_income_tax, get_public_holidays, list_series). Only 'settlement_date' is a noun phrase but still clear.

Tool Count5/5

10 tools cover a well-scoped domain of economic reference data without bloat. The count feels appropriate for the server's purpose.

Completeness4/5

Covers core areas: wage, tax, VAT, holidays, series, settlement dates. Minor gaps exist (e.g., no social security or currency data), but the scope is clearly defined and noted.

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