formula_pk_models

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

With no annotations provided, the description must carry the full burden. It discloses the return type ('Returns: 藥動學模型列表') and the external source (BioModels), but it does not mention any potential side effects, error conditions, or network behavior. For a search tool, this is adequate but not rich.

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 with a clear header, Args, Returns, and Example sections. Every line provides useful information without redundancy. It is appropriately sized for a simple search tool.

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 description covers the tool's purpose, parameters, return type, and examples. Since an output schema exists, it doesn't need to detail return fields. It lacks only explicit guidance on alternatives or potential edge cases, but overall it is complete for a search tool.

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 0%, so the description compensates fully by explaining each parameter: query as search keyword with examples, drug as optional drug name, and limit as maximum returns. The Examples section further illustrates parameter usage, adding clear semantic meaning.

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 purpose: '搜尋藥動學 (PK) 模型' (search pharmacokinetic models) and specifies the source '專門從 BioModels 搜尋藥動學相關模型' (specifically search PK-related models from BioModels). This distinguishes it from generic formula search tools like formula_search.

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 context on when to use the tool via examples (query='absorption', drug='warfarin') and specifies it is specialized for PK models from BioModels. However, it does not explicitly mention alternatives or exclusions, so it falls short of a full 5.

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