futures_hog_supply

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the source URL and return type (DataFrame), which are useful but not deep behavioral traits like refresh frequency, pagination, or data coverage. This is adequate given the 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 uses a structured docstring format, but is somewhat redundant: '玄田数据-供应维度' appears in both the purpose and the return description, adding no new information. The return type information is useful, and the parameter list is necessary, but the overall structure could be tightened with a clearer upfront statement of the tool's function.

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?

With only one parameter and rich annotations, the tool is relatively simple. The description provides the parameter choices, return type, and source URL. However, with no output schema, it does not describe the specific columns or units of the returned DataFrame, and it fails to differentiate from siblings. It is minimally complete but leaves gaps for an agent.

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 coverage is 0% and no enum is defined in the schema, so the description's explicit list of allowed values for the 'symbol' parameter is critical. It provides a clear enumeration of options, which helps an agent invoke the tool correctly. It does not explain what each symbol represents semantically, but the names are reasonably descriptive.

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 identifies a specific resource ('supply dimension' data from 玄田数据) and indicates the return type (pandas.DataFrame) and parameter choices. While there is no explicit verb like 'fetch' or 'list', the intent is clearly data retrieval. It does not, however, distinguish this tool from the many sibling hog-related tools.

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 no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or scenarios where a sibling tool (e.g., futures_hog_core, spot_hog_soozhu) would be more appropriate. Usage context is only implicit via the parameter choices.

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