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

Annotations declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description does not need to restate safety. The description adds value by specifying the return shape ({valid, name, address, vat_number, country}), which complements the annotations and output schema. It also mentions 'Real-time' and 'VIES (27 countries)', providing context beyond annotations. No contradictions.

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 sentence (plus a return type snippet) that is fully front-loaded. Every word provides value: 'Real-time', 'EU VAT validation via VIES (27 countries)', and the return structure. No wasted or redundant 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?

The tool has a clear purpose, good annotations, and an output schema. The description adds the VIES source and return fields, making it complete for most common use cases. However, it does not address edge cases like VIES unavailability (common in production) or the fact that no parameters are required (a subtle issue). Given the tool's simplicity, this is slightly incomplete but still strong.

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%—all three parameters (q, vat, query) are documented in the schema with examples and descriptions. The tool description does not add any parameter-specific meaning beyond what the schema provides, such as clarifying when to use each alias. Baseline 3 is appropriate since the schema does the heavy lifting.

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 ('validate'), a specific resource ('EU VAT'), and names the authoritative source ('VIES (27 countries)'). It distinguishes itself from sibling tools (e.g., entity_lookup, professional_lookup) by focusing on VAT validation rather than entity searches or risk audits. The one-line purpose is immediately clear.

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 this is for real-time VAT checks against EU countries, but provides no explicit guidance on when to use it versus alternatives (e.g., when to prefer this over entity_lookup for VAT data). There are no exclusions or prerequisites stated, such as requiring a specific VAT format or noting VIES downtime. The context is clear but lacks 'when-not' details.

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