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Xearno Tools

Netherlands 30% Ruling Calculator — 2027 changes

netherlands_30_percent_ruling
Read-only

Whether you qualify for the Dutch 30% ruling, how much of your salary comes tax-free, and what changes when it drops to 27%. Whether the Dutch 30% ruling is worth 30% to you or 27% depends on one thing: the year it was first granted. Granted in 2023 or earlier and it stays at 30%, on the old salary threshold, for its whole term. Granted in 2024 and it falls to 27% in 2027 but keeps that old threshold. Granted from 2025 and it is 27% on the higher threshold from the start. General-purpose AI collapses all of this into “it’s 30%” or “it’s being scrapped”, and for most people both are wrong. The questions that actually decide it are narrow — when your ruling started, whether you lived more than 150km from the Dutch border before you moved, and how many months you had already spent in the country — and this asks them, then works out what comes to you tax-free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoComputation year The rate (30% → 27%) and the salary norms change at the 2026/2027 boundary — differently per cohort.2026
cohortNoWhen was (will) your 30% ruling first granted? The decisive input. The 2027 transition is THREE cohorts, not two: 2023-and-earlier keep 30% AND the old salary norm for their full term; 2024 starters drop to 27% in 2027 but KEEP the old norm; 2025-and-later starters get 27% AND the higher norm from 2027.new
salaryNoAnnual gross salary (total compensation) (€) Your total agreed gross pay, before the tax-free allowance is carved out of it. The salary norm tests what remains TAXABLE after the allowance — the tool handles that split.
distanceOkNoLived >150km from the Dutch border before starting? A hard eligibility gate: you must have lived more than 150km from the Dutch border for more than 16 of the 24 months before your Dutch employment began. This excludes Belgium, Luxembourg, and border regions of Germany.yes
priorNlMonthsNoMonths lived or worked in NL in the past 25 years (mo) Earlier stays in the Netherlands within the last 25 years are deducted from the 60-month maximum duration.
under30MastersNoUnder 30 with a (Dutch-equivalent) master’s degree? A lower salary norm applies (€36,497 vs €48,013 in 2026) — but only until the month you turn 30.no

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description's job is to add context. It does so by explaining the cohort-dependent logic, the decisive questions (start date, distance, prior months), and the output ('what comes to you tax-free'). This adds value beyond the read-only hint without contradicting it.

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?

The description is a single, lengthy paragraph with useful information, but it includes a meta-commentary about general-purpose AI that is not strictly necessary for tool invocation. It is front-loaded with the core purpose and structured logically, but could be more concise without losing value.

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 complex calculator with 6 parameters and no output schema, the description does a good job of explaining the tool's scope, the 2027 changes, and the decisive inputs. It implies the output (qualification and tax-free amount) even if it doesn't detail the exact return structure. The read-only annotation and thorough schema help complete the picture.

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% with very detailed parameter descriptions. The tool description adds a narrative that highlights the key inputs (cohort, distance, prior months) but does not provide additional syntax or format details beyond what the schema already offers. This aligns with the baseline of 3 for full schema coverage.

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 explicitly states the tool's purpose: determining qualification for the Dutch 30% ruling, the tax-free portion of salary, and the impact of the 2027 rate drop. It distinguishes itself from sibling tools by focusing on the specific 30% ruling and its cohort-based 2027 changes, using specific verbs like 'qualify' and 'works out'.

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 provides clear context for when to use the tool, emphasizing the nuanced cohort rules and warning that general-purpose AI often gets it wrong. However, it lacks explicit exclusions or alternative tool references, relying on the reader to infer this is the dedicated tool for this calculation.

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
Disambiguation4/5

Each tool targets a distinct niche (e.g., specific country tax rules, loan types, or legal calculations), with detailed descriptions that clarify boundaries. However, the large number of tools (66) could cause some confusion for an agent trying to select the right one for a general query, especially when multiple tools relate to the same country.

Naming Consistency4/5

Tool names follow a mostly predictable pattern: lowercase words separated by underscores, often starting with a country name (e.g., 'uk_stamp_duty_sdlt') or a topic (e.g., 'compound_growth'). There are minor deviations, such as abbreviations ('npv_irr', 'sip') and varying use of verbs, but overall the naming is clear and consistent.

Tool Count3/5

At 66 tools, the server is unusually large and covers an extensive range of financial and legal calculators. While each tool justifies its existence, the count exceeds the typical well-scoped range (3–15), making the server feel bloated. A more modular design might improve coherence.

Completeness4/5

The tool set covers a wide array of domains: personal income taxes, property taxes, loan calculations, investment returns, and specific country regulations. Minor gaps exist (e.g., missing tools for corporate taxes, general retirement planning, or insurance), but the overall coverage is thorough and addresses many niche scenarios that general AI handles poorly.

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