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.