spot_corn_price_soozhu

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds the return type (:rtype: pandas.DataFrame) and a source URL (https://www.soozhu.com/price/data/center/), which are useful behavioral details beyond the safety annotations. It does not cover pagination or rate limits, but the return-type disclosure earns a strong score.

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, containing only the title, source URL, return description, and return type. Every line provides useful context with no filler or redundant text. This is perfectly sized for a zero-parameter read-only 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?

For a zero-parameter read-only data tool, the description provides essential information: the data subject (national corn price trend), the source (Soozhu), and the return type (pandas.DataFrame). However, it lacks detail on the DataFrame's columns, date range, or frequency. Given the absence of an output schema, a bit more structure would be ideal, but the tool's simplicity and strong annotations keep it at a 4.

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 tool has zero parameters, so the rubric sets a baseline of 4. The input schema is empty and trivially 100% covered, so there is no parameter information for the description to add. The description need not compensate for missing parameter details.

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 as '全国玉米价格走势' (national corn price trend) and notes it returns a pandas DataFrame, making it evident this tool provides corn price trend data from Soozhu. It distinguishes from sibling tools like spot_hog_soozhu by the 'corn' resource, but lacks an explicit verb such as 'get' or 'retrieve', so it is not a perfect 5.

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?

There is no guidance on when to use this tool versus alternatives. It does not mention that it complements or differs from related Soozhu price tools (e.g., spot_soybean_price_soozhu, spot_hog_soozhu), nor does it describe appropriate contexts or prerequisites. The only implied usage comes from the tool name and resource description, which is insufficient.

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