会社法人等番号から法人番号を算出

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently explains input normalization (full-width digits, hyphens, spaces), explicitly warns about the personal number misuse risk, and discloses the limitation that it cannot determine number type. It does not describe the exact return format, but the purpose statement implies the 13-digit output, and no side effects are relevant for a pure calculation.

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 three sentences, each earning its place: the first states the purpose, the second covers input normalization, and the third provides a crucial safety warning. It is front-loaded and free of redundancy, achieving maximum clarity in minimal space.

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?

Given the tool's simple nature (single parameter, calculation-only, no output schema), the description covers all essential aspects: purpose, input normalization, limitations, and safety guidance. It does not need to explain return values in detail because the purpose sentence clearly indicates the output, and there are no complex side effects or prerequisites. Sibling tool relationships are not explicitly addressed, but the tool's own capability is clearly delineated.

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% for the single parameter, but the tool description adds significant value beyond the schema by detailing normalization rules (full-width, hyphens, spaces) and the safety constraint about personal numbers. This extra semantic context helps the agent correctly format input and avoid dangerous misuse.

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 specific action (calculate check digit) and resource (company corporate number to 13-digit corporate number). It distinguishes itself from sibling tools like validate_corporate_number and parse_corporate_number by focusing on calculation and explicitly noting it cannot determine number type, which is a key differentiator.

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?

The description provides clear context: it is for converting a 12-digit company corporate number to a 13-digit corporate number and handles normalized input. It gives an explicit when-not guidance by warning against inputting personal numbers because the tool cannot distinguish types. However, it does not name alternative tools for validation or parsing, so it stops short of a 5.

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