taiwan_validate_tax_id

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

With no annotations, the description fully discloses behavioral traits: it is a pure algorithm (no database), returns valid and explanation, and cites the data source. This gives the agent full understanding of what to expect.

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 extremely concise: two sentences plus a data source. The first sentence states the core function immediately, and every sentence provides necessary information without waste.

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 validation tool with one parameter and no output schema, the description is complete. It explains the algorithm, purpose, and return value, leaving no gaps for the agent.

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 sole parameter 'unified_business_no' has a description that adds value beyond the schema: it specifies the format (8 digits) and provides an example. Since schema coverage is 100%, baseline is 3, but the added context justifies a 4.

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 it validates the check digit of Taiwan's unified business number using an algorithm, specifying the length (8 digits) and that it is pure algorithm without database lookup. It also mentions usage for data cleaning and form validation, distinguishing it from sibling tools like taiwan_company_verify.

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 use cases: data cleaning, form validation, and checking valid format. However, it does not explicitly state when not to use it or compare with alternatives like taiwan_company_verify, leaving some ambiguity for the agent.

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