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Total Cost of Living vs Your Income

compare_total_cost
Read-onlyIdempotent

What a month actually costs in each of 41 countries on a stated income, and what is left over. Sums four lines that are kept from overlapping: rent (measured Eurostat city rents, HUD Fair Market Rents, or the price basket where neither covers a country), the everyday basket EXCLUDING rent (the basket normally contains rent — roughly half of it — so adding a separate housing figure to the full basket would overstate a total by ~60%), out-of-pocket healthcare, and income tax plus employee social contributions on that income. VAT is already inside the basket prices (purchasing-power data derives from surveyed purchaser prices) and is therefore never added. Tax assumes you become tax-resident and are taxed locally, single filer, no deductions; special regimes such as Portugal's IFICI are reported separately where they would be cheaper. Estimates for comparison — not a quote and not tax advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoRanking. 'remaining' = most left over first; 'share' = smallest share of your income.total
incomeYesMonthly income in USD. Required — the tool is a subtraction.
countryNoISO 3166-1 alpha-2; echoes that country's row and rank as `focus`.
maxPctOfIncomeNoKeep only countries whose total is at or below this share of income (%).

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses significant behavioral details: four cost lines are deliberately kept non-overlapping, rent is excluded from the everyday basket to prevent ~60% overstatement, VAT is already included and never added, and tax assumptions are spelled out (tax-resident, single filer, no deductions, IFICI handled separately). This gives an agent an accurate model of how results are computed.

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 description is dense but front-loaded: it leads with the core result, then explains methodology and caveats in a logical order. Every section earns its place given the complexity of the calculation, though it is somewhat long for a tool with a simple required parameter.

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 tool with no output schema, the description covers the essential return concept (monthly cost and leftover), data sources, exclusions, tax assumptions, and scope limits across 41 countries. It stops short of describing the exact response shape or sorting mechanics, but the input schema covers sort behavior and the overall picture is complete enough for correct invocation.

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 the baseline is 3. The description adds context for income ('the tool is a subtraction') and clarifies what cost components the total comprises, but it does not add much detail about sort values, country format, or maxPctOfIncome beyond what the schema already states.

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 opens with a specific outcome: what a month actually costs in each of 41 countries on a stated income and what is left over. It then names the four cost components (rent, everyday basket excluding rent, healthcare, income tax) and the subtraction logic, making the tool's scope distinct from broader siblings like compare_countries or compare_housing.

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?

The description gives clear usage context: it is for comparing monthly total living costs against a stated income across 41 countries, with explicit caveats that it is an estimate and not a quote or tax advice. It does not explicitly name when to prefer an alternative sibling, but the domain and boundary conditions are clear enough for an agent to route correctly.

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

A3.9/5.0
Disambiguation3/5

Several tools occupy adjacent territory: check_travel_residency explicitly supersedes check_residency, check_schengen, and check_tax_residency_risk, and the cost-of-living family (arrival_cost, compare_total_cost, compare_housing, estimate_micro_costs, calculate_ppp, localize_salary) has overlapping price-level concepts. The detailed descriptions mostly clarify boundaries, but an agent selecting by name alone could easily pick the wrong residency or cost tool.

Naming Consistency4/5

Most tools follow a clean verb_noun snake_case pattern with recognizable prefixes (compare_*, check_*, find_*, calculate_*), which makes the set predictable. Deviations like arrival_cost, passport_power, required_rate, and the acronym-heavy calculate_ppp keep it from being perfectly uniform.

Tool Count3/5

26 tools is a heavy surface, and at least three of the check_* tools are explicitly superseded by check_travel_residency, adding redundant weight. The broad geo-arbitrage/nomad domain justifies much of the breadth, but the set feels closer to a full toolkit than a focused server.

Completeness4/5

The toolset covers the core remote-work and geo-arbitrage decision space: cost of living, purchasing power, tax residency risk, nomad visas, housing, healthcare, climate, connectivity, holidays, salary localization, FIRE, livability, and even team timezone planning. Gaps are minor—no family-size cost tool, no immigration/citizenship pathway data, and no dedicated safety/crime dataset beyond the livability composite—but agents can work around them.

Resources