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

Annotations are empty, so the description carries the full burden. It discloses the core validation behavior (format + mod-97 checksum), but does not mention return format, potential side effects (none expected), or edge cases like whitespace handling. The description adds essential context but is not exhaustive.

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, focused sentence that front-loads the action and includes necessary detail. No wasted words, and it is easily scannable.

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 simple validation tool with one parameter and no output schema, the description is nearly complete. It explains what validation is performed. However, it omits the exact return value or type (e.g., boolean vs. detailed report), which could be inferred but is not stated.

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 describes the parameter 'iban' with an example. The description adds meaning by specifying what 'valid' entails (format + mod-97), enriching the schema's basic description. Since schema coverage is 100%, the added context raises it above baseline.

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 the tool's function: 'Vérifie si un numéro IBAN est valide' (checks if an IBAN is valid). It specifies the validation includes format and mod-97 checksum, which provides precise scope and distinguishes it from any potential 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?

While there are no sibling tools to contrast with, the description implies the use case: validating an IBAN. It does not explicitly mention when not to use it or alternatives, but the purpose is self-evident. Lacks explicit exclusions or alternative references.

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