VAT Validator MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that VAT rates 'change without notice and cannot be sourced from training data,' which is a key operational caution. It also states the return content ('current standard and reduced VAT rates'). It doesn't mention potential errors or rate limits, but the read-only nature is clear.

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 somewhat lengthy, but every sentence carries purposeful guidance: the main action, usage timing, workflow context, compliance rationale, and an explicit decision rule. It is front-loaded with the core function ('Retrieves current VAT rates') and remains focused despite the extra detail. Not excessively verbose for the value it provides.

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?

This is a simple tool with one optional parameter, yet the description covers the what, when, why, and output ('standard and reduced VAT rates'). It also provides a compliance warning and a behavioral rule. Combined with the existing output schema, no critical information is missing for an agent to select and invoke the tool correctly.

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?

The schema already documents the country_code parameter (100% coverage). The description adds value by indicating where to obtain the parameter: 'passing the country_code from that response' (from validate_vat), and reinforces the optional behavior with 'Omit for all countries' which is already in the schema. This linkage to the sibling tool enriches the parameter semantics beyond the schema alone.

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 function: 'Retrieves current VAT rates for a jurisdiction.' It uses a specific verb and resource, and explicitly frames it against the sibling tool validate_vat ('or immediately after validate_vat'), which distinguishes it.

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 gives explicit when-to-use instructions: 'Call this BEFORE calculating any invoice total or approving any VAT amount -- or immediately after validate_vat.' It also provides a concrete use case (verifying supplier invoice rates) and a decision rule ('If the rate on the invoice differs from the rate returned here, do not approve payment').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description fully discloses behavior: it validates against EU VIES and AU ABR live registries, returns a PROCEED/VERIFY_MANUALLY/HOLD verdict with fraud risk score and name-match check. It also reveals critical downstream consequences (unrecoverable tax liability for invalid VAT, rejection at mandate platforms) and states the tool is a one-call, machine-ready verdict, providing complete transparency about its operation.

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 front-loaded with the core purpose and then expands into timing, registries, returns, and consequences. While it is longer than typical descriptions, the added length is justified by the compliance-critical context. There is minor redundancy between 'Call this BEFORE...' and 'Use this when...', but overall structure is logical and every section adds meaningful information.

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?

Despite having no annotations, the description is highly complete: it covers the exact use case, timing, data sources, return format, risk implications, and integration with a sibling tool. For a tool with three parameters and an output schema (not shown), this description fully equips an agent to select and invoke the tool correctly, even without seeing the output schema.

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?

Schema coverage is 100%, and the schema descriptions already explain invoice_amount and invoice_company_name. The description adds value by connecting the response (country_code) to the sibling tool get_vat_rates, and it mentions the fraud risk weighting indirectly, enriching the parameter context beyond the schema. This justifies a score slightly above the baseline of 3.

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 opens with a specific verb ('Validates') and object ('VAT number against live government registries'), making the core function immediately clear. It also distinguishes itself from the sibling tool by explicitly referencing how to pass country_code to get_vat_rates, showing where this tool fits relative to alternatives.

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 gives explicit timing instructions ('Call this BEFORE submitting any B2B payment...') and describes the exact trigger ('when a supplier invoice carries a VAT number...'). It also names specific integration points (Stripe MPP, Alipay AI Pay, Shopify UCP) and explains the relationship to get_vat_rates, leaving no ambiguity about when to use this tool versus the sibling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.