spot_hog_year_trend_soozhu

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds the return type (pandas.DataFrame) and the URL as data source, but does not disclose behaviors like update frequency, timezone, or missing data handling. It does specify the time period ('今年以来') which is useful, but not beyond what the tool name implies.

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 compact: a title line, a URL, and a docstring-style return type. It is front-loaded with the main meaning, but the title line and the :return: line repeat the same phrase '今年以来全国出栏均价走势', creating slight redundancy. Still, it is efficient overall.

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?

This is a simple no-parameter tool with annotations covering safety, but there is no output schema. The description tells the agent it returns a DataFrame of the national average price trend since the start of the year, but lacks details such as frequency (daily/monthly), units, or column names. It is adequate for a basic data fetch but not fully complete.

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?

There are 0 parameters and the schema coverage is 100%, so under the rubric the baseline is 4. The description reinforces that no inputs are needed and clarifies the output is a DataFrame of the year's trend, which adds minimal meaning 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 tool as providing the national slaughter average price trend since the beginning of the year from Soozhu's pig big-data platform. It specifies the exact resource (全国出栏均价走势) and the source URL, distinguishing it from sibling soozhu tools that provide spot prices or other hog-related metrics.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention exclusions or compare to sibling tools such as spot_hog_soozhu or index_hog_spot_price. Usage is only implied by the data description, not stated.

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