vatAdd or remove VAT at any rate — including the divide-not-subtract trap. Adds VAT to a net price or extracts it from a gross price at any rate. The extraction direction is where invoices go wrong: removing 20% VAT means dividing by 1.2, not subtracting 20%.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | Direction | add |
| rate | No | VAT rate (%) UK 20 · DE 19 · FR 20 · ES 21 · IT 22 · NL 21 · SE 25 · CH 8.1 · AE/SA 5/15 | |
| amount | No | Amount |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the two operational modes (adding VAT to net price or extracting from gross price) and the correct calculation method. It adds behavioral context beyond the readOnlyHint annotation by describing the non-destructive mathematical operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loading the core purpose and common pitfall. Every word adds value, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and full schema coverage, the description is complete. It clearly explains the calculation direction and warns about a common error. No output schema is needed as the result is a straightforward numeric value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While all parameters have schema descriptions (100% coverage), the description enriches the meaning by explaining the mode direction ('adds VAT to a net price or extracts it from a gross price') and providing country-specific rate examples. It also clarifies the common mistake for the removal operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: adding or removing VAT at any rate. It uses specific verbs ('Add or remove') and identifies the resource ('VAT'). It distinguishes itself from sibling financial calculators by focusing on VAT calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool (for VAT calculations) and offers practical guidance on the correct mathematical operation, specifically warning about the 'divide-not-subtract trap'. However, it does not explicitly exclude alternative tools or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.