Geo-Parity

One country, every hub: the headline figures

country_dossier

Read-onlyIdempotent

The three to six headline figures each hub owns for one country, in one call: price level vs the US and datasets covering it (compare); monthly essentials, health out-of-pocket spending and — with income — what is left after costs (costs); modelled median and minimum wage, ILOSTAT measured median, pension replacement rate (earn); safety and healthcare-access scores, rule of law, disaster risk, comfortable days, tax-residency threshold, passport rank, nomad-visa programmes (move); public holidays, latency and download speed, employer contribution loading, weekly hours, paid maternity leave (work); inflation, policy rate, banked adults, remittance corridors surveyed (money); combined corporate tax rate, top income-tax rate and where it starts, standard VAT rate (absent for the US — state sales taxes are not a 0% VAT), the Women, Business and the Law index and retirement ages for men and women (rules); FCDO and US State Department advice levels, the yellow-fever certificate position, homicide rate and PM2.5 exposure with their years (safety); retirement ages for men and women (OECD, else WBL), the net replacement rate, life expectancy and the kind of retiree visa (retire). Effective average corporate tax rate, standard withholding on dividends, days to register a company (absent outside the B-READY cohort) and the kind of founder visa (business). Since 5 Sep 2026 the sections also carry doctors per 10,000 (safety), the couple's net childcare cost as a share of income (costs), days for imports to clear customs and hours on tax compliance (business), the E-Government index (work), and the foreign-ownership band for property and the kind of student visa (move) — each absent where its source does not cover the country. Every figure carries the id of the source that produced it, tools names the MCP tool to call for detail per section, and sources lists only what was actually included. A section or figure the site has no data for is ABSENT, never null — Thailand has no OECD employer rate and no holiday calendar, so its work section lacks those keys. About 5-8 KB. Built for agents that would otherwise call a dozen tools to answer "tell me about moving to Portugal". From 13 Sep 2026 rules also carries minAnnualLeaveDays and noticeEmployerMinWeeks (tool employment_rules) and safety carries drivesOn and bacLimitPct (tool driving_rules), each absent where the register sets none.

Input Schema

Name	Required	Description	Default
`income`	No	Gross monthly income in USD. Optional; unlocks the total-cost figures.
`country`	Yes	ISO alpha-2 code (e.g. "PT").

Output Schema

Name	Required	Description	Default
`ok`	No
`tools`	No
`country`	No
`sources`	No
`updated`	No
`sections`	No
`attribution`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 1, 2026

addedInput schema / examples

Added value: +[
+  {
+    "country": "PT",
+    "income": 5000
+  }
+]

AddedSep 4, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Beyond the annotations, it discloses crucial behavioral traits: absent data is omitted rather than null, every figure carries a source id, `tools` names the per-section detail tool, and `sources` lists only included material. It also states output size, date-based additions, and concrete absence examples. There is no contradiction with the read-only/idempotent annotations.

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

Conciseness3/5

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

It is front-loaded with a useful summary, but then becomes an extremely dense run-on enumeration of sections, fields, and date-specific additions. Much of that return-value detail is already available through the output schema, so the description is longer than necessary and harder to scan.

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?

Given the tool's breadth, the description is complete: it covers what is returned, how absences work, optional income effects, provenance, and the post-2026 additions. With an output schema present, all remaining gaps are fully addressed.

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 both parameters are already documented in the schema. The description reinforces that `income` unlocks total-cost figures but adds little syntax or format meaning beyond what the schema provides.

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 precise resource and scope: the three-to-six headline figures each hub owns for one country, returned in a single call. It enumerates every topic section covered, making it unmistakable as an aggregate overview tool distinct from single-topic siblings.

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 gives a clear use case — agents that would otherwise call a dozen tools to answer broad questions like 'tell me about moving to Portugal' — and implies that per-section detail should be fetched through the MCP tools named in the `tools` field. It does not explicitly name when to prefer specific comparison siblings, so it stops short of full when/when-not guidance.

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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