Generate test IBAN

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

No annotations are provided, so the description carries the burden. It does usefully disclose the output guarantee (mod-97 valid) and the safety caveat (not a real bank account), but adds nothing about determinism, randomness, or how the result should be handled.

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 short sentences, zero waste, with the output guarantee and the disclaimer front-loaded.

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 zero-required-parameter generator with no output schema and complete parameter documentation, the description covers what the tool does and its safety profile. Only minor gaps (return format, randomness) remain.

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% and the single optional parameter's allowed values are fully enumerated in the schema, so the description cannot add much beyond it. It offers no country-selection detail, so baseline 3 applies.

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 ... IBAN') and qualifies it as a mod-97 valid TEST value, which immediately distinguishes it from any real-banking sibling concept. An agent knows exactly what it produces.

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?

No when-to-use or when-not-to-use guidance and no mention of alternatives among the other generators. The 'TEST' qualifier implies test-data usage but only by inference.

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