taiwan_company_rankings

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

No annotations are provided, so the description carries full responsibility. It discloses the data source (inc.com.tw), mentions sub-string matching for industry, and clarifies county name formatting (use '臺' not '台'). This adds transparency beyond the schema.

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 a single well-structured sentence that front-loads the main function and then provides filtering details. It is concise without missing critical information, though it could be slightly more structured with bullet points.

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 low complexity (4 optional parameters, no output schema), the description adequately covers the tool's behavior and usage. It explains the ranking order and filtering, which is sufficient for an agent to decide when to invoke.

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%, but the description adds value by explaining the 'by' enum options (newest/oldest), noting the sub-string matching behavior for industry, and warning about the correct character for 'Taipei'. This enriches understanding beyond the schema.

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 lists Taiwanese company rankings by capital (default), newest, or oldest, with filtering by industry keyword and county. It specifies the data source and gives example queries, making the tool's purpose unambiguous.

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 explicitly states the tool is for answering questions like 'which companies have the largest capital in a certain industry/county?' It does not explicitly exclude alternatives, but the context signals and sibling tool names imply other tools for different queries.

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