商品领航员

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

With no annotations provided, the description carries the full burden, and it does disclose the primary behavior: returning a list with specified performance metrics. However, it does not mention operational aspects such as sorting order, pagination behavior, whether the data is live or cached, or any side-effect-free read guarantee. The '列表' wording implies a read operation, but the description could be more explicit for a tool with no annotation coverage.

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, information-dense sentence with a colon introducing the metric list and a clear purpose clause at the end. There is no filler, and every segment—scope, output metrics, and intended use—earns its place.

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 no output schema and no annotations, the description does a solid job listing the return fields and the practical purpose. Minor omissions exist, such as explicit sorting semantics and pagination response behavior, but the tool is a straightforward paginated list, and the schema covers pagination inputs. It is complete enough for an agent to invoke and interpret the result at a basic level.

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 schema already gives meaningful descriptions for 'shop' and 'goodsName', and pageNo/pageSize have default values and constraints, so half of the parameters are sufficiently documented. The description itself adds no parameter-level detail, such as how filtering by goodsName interacts with the store-wide scope or how pagination affects the list. This is adequate but not compensating 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 identifies the resource (store-wide product navigator list) and the specific metrics returned per product, including composite score percentile, refund rate, and stock status. It also states the intended use case ('用于找出拖后腿的商品'), which distinguishes it from sibling tools like pdd_goods_data and pdd_goods_detail by focusing on comparative performance indicators rather than raw product data.

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 gives a clear contextual use case: finding underperforming products through a storewide navigator list. It does not explicitly mention alternatives or when not to use this tool, but the distinctive metric list and store-wide framing make the appropriate scenario reasonably clear.

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