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

With no annotations, the description carries the full burden, and it does disclose meaningful behavior: output is entirely synthetic, never real or registered, and passes real validators (IBAN mod-97, Luhn). This preempts privacy concerns an agent might have. It does not, however, describe output structure or the seed/count semantics, which the schema handles.

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 tight sentences, front-loaded with the core purpose and scope, then the spec grammar and the synthetic-data guarantee. No filler; every clause 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?

No output schema exists, so the description must convey what comes back; it explains the synthetic/format-true nature of values but not the row/column shape or the json/csv distinction (the latter is in the schema). For a generation tool with five parameters it is nearly complete, missing only return-shape detail.

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% (baseline 3), and the description adds conceptual meaning beyond the schema examples by defining the selector taxonomy: a field key like 'phone', 'person' as a full coherent record, and 'preset:<key>' as a scenario. This clarifies the required spec parameter's grammar rather than merely repeating examples.

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?

States a specific verb+resource ('Generate ... synthetic test data for a country') that clearly distinguishes it from the list/fetch/describe/schema siblings. An agent can immediately tell this is the data-producing tool rather than a metadata 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 spec-format explanation implies when the tool is used, but there is no explicit when-to-use or when-not-to-use guidance and no naming of alternatives (e.g., sampuli_schema or sampuli_describe_country for discovering valid specs). Usage context is real but left to inference.

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