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

With no annotations, the description supplies the core behavior: the check is the Luhn algorithm. It does not mention return format, accepted input formatting, or error behavior, but it is not misleading and gives the key algorithmic trait.

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 short and front-loaded, with no wasted sentences. However, the leading 'Card Validator:' is redundant with the rest of the sentence and the description is too sparse to offset the missing schema.

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 tool with no output schema and no annotations, the definition should state both input mechanism and return behavior. It states the algorithm only, leaving the method of calling the tool and interpreting results unknown.

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 input schema is empty despite the tool logically requiring a card number, and the description never states how or under what parameter name the card number is supplied. An agent has no way to construct a valid invocation from this 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 identifies a concrete operation: validating a credit card number, and names the exact algorithm (Luhn). This is enough to know what the tool does, though it does not explicitly contrast with the many sibling validator 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?

There is no guidance on when to choose this tool over overlapping siblings such as credit-card-validate, validate-credit-card, is-credit-card, or is-credit-card-valid. The intended use is only implied by the word 'validate'.

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