vat.support VAT Compliance

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

With no annotations provided, the description carries the behavioral burden and handles it well: it discloses VIES validation, the production of a printable certificate, and the conditions that yield INELIGIBLE (same-country, non-EU, invalid VAT). It does not mention external dependency failures or output formatting, but the core behavior is clearly disclosed.

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?

Two dense sentences with no filler. The central verdict, VIES check, certificate output, and key ineligibility conditions are all front-loaded and every sentence earns its place.

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?

The description covers the main decision logic and VIES dependency, but there are gaps: customer_vat_id is described as validated yet is optional in the schema, and there is no output schema or return-structure clarification. An agent might not know what happens if customer_vat_id is omitted or what the certificate payload looks like.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining that customer_vat_id is validated via VIES and that country values determine eligibility (same-country, non-EU). This helps the agent understand how the parameters interact.

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 states a specific verb ('Generate') and a precise resource ('EU Art. 196 reverse-charge eligibility verdict for a B2B service invoice between two EU Member States'). It also distinguishes itself from sibling VAT tools by focusing on an eligibility verdict plus a printable certificate, not just a VAT-number check or rate lookup.

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 a clear target scenario—B2B services between two EU Member States—and states when INELIGIBLE is returned. However, it does not explicitly route the agent away from sibling tools like vat_compliance_full or vat_number_check, nor does it name alternatives or exclusion criteria.

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, the description carries the responsibility for disclosing behavior. It clearly describes what the analysis returns: compliance score (0-100), risk band, itemised findings with Article citations, and source verification per finding. It does not explicitly state side-effect status, but a gap analysis is inherently a non-mutating evaluation.

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 one sentence, front-loaded with the action and resource, and concisely lists the key return elements without fluff. Every phrase earns its place.

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?

Since there is no output schema, the description's breakdown of return values is essential and well provided. The input schema fully documents parameters. It lacks explicit alternative tool guidance, but for a single-purpose analysis tool the overall description is largely complete.

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 description coverage is 100% and the schema already explains the answers object and language parameter, including Q1..Q10 format and accepted legacy strings. The tool description only reinforces the 10-question structure and does not add meaning beyond the schema.

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 uses a specific verb ('Run') and a specific resource ('full 10-question VAT compliance gap analysis'). It clearly distinguishes this as a comprehensive analysis tool versus the narrower sibling tools like vat_number_check or vat_rate_lookup.

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 states the tool runs the full 10-question analysis but gives no explicit guidance on when to choose this over alternatives such as vat_registration_check or reverse_charge_certificate. The word 'full' implies comprehensive use, but no when-not conditions or selection criteria are provided.

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 carries the full burden. It discloses the core behavior (external validation via VIES/HMRC and returning name/address when available), but it does not mention possible failures, network dependency, latency, or what happens for invalid or unregistered VAT numbers.

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 two sentences with no filler. It front-loads the main purpose and adds the key return detail without unnecessary elaboration.

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?

For a simple single-parameter tool, the description covers the essential information: what is validated, against which systems, and what is returned. It lacks explicit sibling differentiation and error-handling details, but nothing needed to invoke it correctly is missing.

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 description coverage is 100%, so the schema already documents vat_id fully, including the country-prefix requirement. The description adds only that the VAT identifier is 'single' and 'EU/UK', which is marginal beyond the schema. Baseline 3 is appropriate.

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 identifies the action ('Validate'), the target resource ('a single EU/UK VAT identifier'), and the validation sources (VIES/HMRC). It does not explicitly distinguish itself from the similar-sounding sibling vat_registration_check, so it misses full sibling differentiation.

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 usage is implied by the description: use it to validate a single EU/UK VAT identifier against VIES or HMRC. However, it does not explicitly state when to prefer this tool over vat_registration_check or vat_compliance_full, nor does it mention any exclusions or alternatives.

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?

No annotations are provided, so description carries the burden. It discloses the data source (EU TEDB) which adds trust/context, but doesn't say whether the lookup hits a live API, returns cached data, or what happens for unsupported countries. Mutating or read-only is implied (lookup is read) but not explicit.

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?

One clear sentence, properly front-loaded with the action and resource. No waste, though it could mention the default rate type explicitly in text to reinforce the schema.

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?

A simple two-parameter lookup with a well-documented schema. The description plus schema covers core usage; no output schema means return format isn't promised, but for a rate lookup it's likely a numeric rate. Missing minor context like coverage scope (EU only?) and response shape, but adequate for basic use.

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 covers 100% of parameters with descriptions (ISO-2 code and enum). Description adds source context but no additional parameter details beyond 'optional rate type'. Baseline 3 is appropriate since schema already explains the parameters well.

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?

Clear verb+resource: 'look up the applicable VAT rate for a country' with optional rate type. It distinguishes itself from a generic lookup by naming the EU TEDB source, but doesn't name any sibling 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?

Implied usage: a lookup tool for VAT rates, with rate_type defaulting to standard. No explicit when/how to choose this over other tools, and no exclusions or context about when it applies (e.g., EU vs non-EU).

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what decision is made but not how thresholds are applied, what output format is returned, or which inputs are actually required versus optional. The description also omits any assumptions, limitations, or country-specific handling details.

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 a single focused sentence with no filler, and it front-loads the core purpose. It is efficiently written, though its brevity means it can't carry the behavioral and parameter detail the tool needs.

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?

With no annotations and no output schema, the description leaves too much unstated. It doesn't describe the return result, threshold logic, or how optional parameters like supply_types and sale_countries affect the decision. It also creates ambiguity by naming customer_type and annual_revenue while only country is required in the 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 description coverage is only 40%, so the description must compensate, but it only mentions customer type and annual revenue as inputs and adds no semantic detail such as thresholds or units. It doesn't clarify the required country parameter or the roles of supply_types and sale_countries. The added value over the schema is minimal.

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 identifies the tool's function: it determines whether a business needs to register for VAT in a country, using customer type and annual revenue as key inputs. This is specific enough to distinguish it from related tools like vat_rate_lookup or vat_number_check, though it doesn't explicitly contrast with siblings such as vat_compliance_full.

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 implies the tool should be used when an agent needs a VAT registration eligibility decision with customer type and revenue available. However, it provides no explicit guidance on when not to use it, no alternative tool recommendations, and no indication of how it fits alongside vat_compliance_full or reverse_charge_certificate.

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