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

With no annotations present, the description carries the full burden and does well: it discloses that answers are 'practitioner-verified,' that it is 'guidance only, not binding advice,' that high-risk cases are flagged for escalation, and that there is a $0.25 cost paid automatically via x402. It could add more about response format or failure handling, but the key behavioral caveats are covered.

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 bit longer than minimal, but every sentence earns its place: the main action, the scope, the usage guidance, the caveat, and the cost. It is front-loaded with the primary purpose and keeps important operational details after the core routing 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?

For a natural-language Q&A tool with no output schema, the description gives the agent enough to decide whether to call it and what to expect: scope, coverage examples, routing trigger, advisory nature, escalation behavior, and pricing. It does not specify return structure, but that is less critical for this general query tool.

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 provides 100% coverage on the single `q` parameter with examples. The description adds value beyond the schema by framing the input as a 'general EU/Italy customs question in natural language' and enumerating the topical scope, which helps the agent craft appropriate queries.

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 and resource: 'Ask a general EU/Italy customs question in natural language and get a practitioner-verified answer.' It clearly situates the tool as a generalist fallback by naming the specialized sibling category ('when you don't know which specialised tool fits'), distinguishing it from the more targeted sibling tools.

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 explicitly tells the agent when to use it: 'Use it when you don't know which specialised tool fits, or for procedural 'how do I…' questions.' It does not explicitly list alternatives by name or state when not to use it, but the generalist-versus-specialist framing provides a clear routing heuristic.

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