Geo-Parity

Measured pay by occupation (ILO), and the gender gap in each

compare_occupation_pay

Read-onlyIdempotent

MEASURED gross monthly earnings of employees by ISCO-08 major occupation group, from ILOSTAT — median and mean, in USD, PPP dollars and local currency, for 35 countries (a median is published for most of them). This is the site's only measured wage series; calculate_wage_bands is MODELLED, and the two are not interchangeable. Each row also carries the female-vs-male pay gap for that occupation (positive means women earn less; negative values are real and are kept) and where the occupation's median sits on the country's modelled national wage ladder. Employees only — excludes the self-employed and informal workers, which is why these diverge most from GNI-derived estimates in countries with large informal sectors. Before tax. The ten ISCO-08 major groups are broad families of work, not job titles: one group covers a surgeon and a junior developer alike. Countries with no ILO data return NO_DATA rather than a modelled substitute.

Input Schema

Name	Required	Description	Default
`country`	Yes	ISO 3166-1 alpha-2 country code (case-insensitive).
`occupation`	No	Narrow the response to one ISCO-08 major group. Omit for the whole table.

Output Schema

Name	Required	Description
`ok`	No
`rows`	No
`year`	No	ILO reference year — one year across every occupation in the country.
`basis`	No	Always 'measured' on success.
`country`	No
`modelRatio`	No	measured / modelled for the country. Above 1: the model understates local pay.
`measuredMedianMonthlyUsd`	No
`modelledMedianMonthlyUsd`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 1, 2026

addedInput schema / examples

Added value: +[
+  {
+    "country": "GB",
+    "occupation": "professionals"
+  }
+]

AddedSep 2, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already cover the read-only/idempotent safety profile, but the description adds real behavioral context beyond them: employees-only scope excluding self-employed and informal workers, pre-tax basis, the sign convention for the gender gap (negative values kept), and the NO_DATA fallback. This is unusually rich disclosure.

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?

Dense and front-loaded: the core purpose, the sibling disambiguation, and the coverage caveats lead. It is longer than strictly necessary and could trim the informal-sector explanation, but nearly every sentence carries distinct decision-relevant information.

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?

With an output schema present, return values need no explanation, and the description still supplies scope, metric units, caveats, and fallback behavior. Nothing an agent needs to call it correctly is missing.

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% and the enum is self-documenting, so the baseline would be 3. The description goes further by warning that the ten ISCO-08 groups are broad families, not job titles ('one group covers a surgeon and a junior developer alike'), which meaningfully shapes how an agent interprets the occupation argument.

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?

States a specific verb and resource: measured gross monthly earnings of employees by ISCO-08 major group from ILOSTAT, with metric variants and country coverage. It explicitly distinguishes itself from calculate_wage_bands as the 'only measured wage series', so an agent can separate it from siblings without opening any schema.

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

Usage Guidelines5/5

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

Names the adjacent tool (calculate_wage_bands) and the exact condition that separates them ('MODELLED, and the two are not interchangeable'), and states that countries without ILO data return NO_DATA rather than a substitute. Use vs. alternatives is fully specified.

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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