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

With no annotations provided, the description carries full burden. It clearly explains the tool's core behavior (validating check digits) and implies a yes/no outcome via usage examples. However, it does not explicitly state the return type (e.g., boolean) or how invalid inputs (like non-numeric strings) are handled, which would be beneficial for full transparency.

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 well-structured and appropriately sized, with a clear opening sentence and organized 'Use when' / 'Do not use when' sections. Every sentence adds value without 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?

For a simple single-parameter tool with no output schema, the description is mostly complete. It explains the purpose, usage, and exclusions. However, it does not explicitly state the return format (e.g., a boolean indicating validity), which would make it fully self-contained for an agent. This minor gap prevents a perfect score.

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% with the parameter 'value' already described as 'Numeric string to validate with Luhn'. The description adds contextual examples ('payment-card-like identifier') but does not add new format or syntax details beyond what the schema provides. Thus the schema does the heavy lifting, and the description meets the baseline without significantly enhancing parameter understanding.

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: running the Luhn checksum on a numeric string to verify the check digit. It uses a specific verb ('Run') and resource ('numeric string'), and distinguishes itself from sibling validators like isbn_validate and uuid_validate.

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?

Explicit 'Use when' and 'Do not use when' sections provide clear guidance on appropriate usage, including concrete examples like 'Does this number pass a Luhn check?' and explicit alternatives for ISBNs, UUIDs, and currency lookup. This fully satisfies the dimension.

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