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

No annotations provided, so description carries full burden. It reveals it's a pure offline computation with a 1-year cache, no network calls after first, and costs $0.001 per call. It also explains auto-detection and input tolerance. This is sufficiently transparent for a read-only validation tool.

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 dense paragraph that front-loads purpose, then provides validation details, example, return fields, performance characteristics, and pricing. Every sentence is informative with no redundancy or fluff.

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?

Given the tool's simplicity (single parameter, no output schema), the description covers all necessary aspects: use case, validation algorithm, input format, output fields, caching, cost, and performance. It is complete for the agent to correctly select and invoke the 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?

Schema coverage is 0% (only type string), but description provides an example query, tolerates spaces/dots/dashes, and explains what the number represents (SIREN vs SIRET). This adds significant meaning beyond the schema's bare 'string' definition.

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 states it pre-validates French company numbers (SIREN/SIRET) for invoicing or before costly API calls. It distinguishes between SIREN and SIRET and mentions specific validation rules (Luhn, La Poste exception), making its purpose distinct from sibling tools like validate_vat_eu or verify_company_fr.

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?

Explicitly recommends use before invoicing or Sirene API calls, providing a clear use case. While it doesn't explicitly state when not to use it or compare to alternatives, the context (offline, fast validation) implies it's for preliminary checks, which is adequate.

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