Xearno Tools

UK Stamp Duty Calculator (SDLT) — England & Northern Ireland

uk_stamp_duty_sdlt

Read-only

What stamp duty you’ll pay on a house in England or Northern Ireland — including first-time buyer relief and the extra on a second home. Stamp duty is not one number attached to a price. Four things can apply at once: the standard bands, first-time buyer relief that takes you to nothing below £300,000, a 5% surcharge that lands on the whole purchase price rather than just the top slice if this is a second home or a buy-to-let, and another 2% if you are buying from abroad. They stack. Two of those changed recently — the bands went back up on 1 April 2025 and the second-home surcharge rose from 3% to 5% in October 2024 — so a general-purpose AI will often hand you a number that was right eighteen months ago and is now thousands of pounds out. Scotland and Wales charge different taxes altogether, LBTT and LTT, and are not covered here.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`price`	No	Purchase price (£) The chargeable consideration — normally the agreed purchase price of the property.
`buyerType`	No	Which buyer are you? The decisive input — it selects the whole rate table. "First-time buyer" means ALL purchasers are first-time buyers: never owned (or part-owned) a dwelling ANYWHERE in the world, including inherited property. "Additional dwelling" means you will own 2+ dwellings at completion and are not replacing a main residence you sold. The two are mutually exclusive by definition — a first-time buyer owns nothing, an additional-dwelling buyer already owns.	moving
`nonResident`	No	Any buyer non-UK-resident? Non-resident for SDLT = present in the UK fewer than 183 days in the 12 months before completion. Adds 2% to every band. On a joint purchase, ANY non-resident buyer makes the whole transaction non-resident.	no

TDQS

A4.3/5.0

Behavior5/5

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

Annotations already mark this as read-only, and the description adds valuable behavior: the four rules stack, the 5% surcharge applies to the whole purchase price, and the rates changed recently (April 2025 and October 2024). This gives an AI agent crucial context about calculation complexity and temporal sensitivity, going well beyond the readOnlyHint.

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?

Four sentences, front-loaded with the core purpose, then expanding into complexity, recency, and scope. Every sentence contains distinct information with no filler, though it is slightly long for a tool description. The structure is logical and easy to parse.

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?

Even without an output schema, the description explains all major input factors (standard bands, first-time buyer relief, second-home surcharge, non-resident surcharge) and their stacking, covers geographic exclusions, and mentions recent rate changes. This is quite complete for a calculator, though it does not specify the exact return format.

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 each parameter (price, buyerType, nonResident) already having detailed, self-explanatory descriptions. The tool description adds overall context about how these factors interact but does not provide additional per-parameter meaning beyond what the schema already offers, so the baseline of 3 is appropriate.

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 it calculates stamp duty for England and Northern Ireland, with the specific verb 'pay' and resource 'house'. It also distinguishes from other tools by explicitly noting that Scotland (LBTT) and Wales (LTT) are not covered, and the full list of factors (first-time buyer relief, surcharge, non-resident) makes its purpose unmistakable.

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 provides explicit when-not guidance: 'Scotland and Wales charge different taxes altogether, LBTT and LTT, and are not covered here.' It also warns that a general-purpose AI may give outdated figures due to recent rate changes, implying that this tool should be used for current SDLT calculations. It does not name a specific sibling alternative, but the scope exclusion is clear.

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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