index_hog_spot_price

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds that the return type is a pandas.DataFrame and provides the source URL, which is some added context. However, it does not disclose data structure, time range, or potential scraping limitations, so it remains modest.

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 short and to the point, with the source URL, return description, and return type. The first line repeats the annotation title, which is mildly redundant, but overall it is economical and front-loaded.

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 tool, the description is too thin. It doesn't explain what columns or index values are returned, whether the data is historical or current, or any interpretation of the index. Even with the DataFrame return type noted, the agent lacks essential context to understand the result.

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 schema is fully self-descriptive. According to the rubric, a baseline of 4 is appropriate; no parameter explanation is needed.

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 states it returns the pig market price index (生猪市场价格指数) from 行情宝 and provides a source URL. This identifies the specific resource, though the verb is implied via ':return:' rather than explicit. It does not distinguish from sibling tools like spot_hog_soozhu, so it misses the top score.

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?

No guidance is given on when to use this tool versus alternative hog price or index tools. There is no mention of prerequisites, scenarios, or exclusions, so the agent receives no directional help.

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