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

No annotations exist, so description carries burden. It explicitly discloses statelessness ('records no decision and leaves no dashboard timeline trace'), providing meaningful side-effect context. It doesn't cover invalid-input error behavior, but for a stateless validator, the key behavioral trait is addressed.

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 crisp sentences, front-loaded with verb and object. No redundant content.

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?

The tool is a one-parameter stateless validator; description covers purpose, output, and side effects. However, it is unclear whether the return value includes a validity indicator or only region+masked form, and invalid input behavior is not addressed, which is a gap given no output schema.

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 only defines parameter name/type with zero description coverage. Description adds semantic meaning: the input should be a Canadian SIN and must pass a Luhn checksum; output is masked. This is enough to understand the single parameter, though exact format constraints are not specified.

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?

Description explicitly states 'Validate a Canadian SIN (Luhn checksum)' and notes outputs, clearly distinguishing this from sibling ID validators (CPF, IBAN, GSTIN) by jurisdiction and algorithm.

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?

It clearly identifies the target input (Canadian SIN) and validation method (Luhn), giving an obvious use case. It does not explicitly name alternatives or exclusions, but the context is unambiguous enough for selection.

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