stock_ipo_benefit_ths

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

Annotations already cover readOnly, idempotent, and non-destructive behavior. The description adds a source URL and return type (pandas.DataFrame), which provide minimal context about data origin and output format, but no additional behavioral specifics such as rate limits, data freshness, or failure modes. There is no contradiction with annotations.

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 very brief with three lines: title, URL, and return type. It is front-loaded with the key resource name and lacks fluff, though the URL is somewhat tangential. It is appropriately sized for a parameterless 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?

Given no output schema, the description provides only a high-level return type and source. It does not specify columns, data granularity, or how the data is structured. For a zero-parameter tool, this is minimally sufficient but leaves gaps for an agent that needs to interpret the returned DataFrame.

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 input schema has zero parameters, so the description needs no parameter details. The schema coverage is trivially 100%, and the description correctly implies a no-argument call. Baseline for zero parameters is 4.

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 returning IPO beneficiary stocks data from Tonghuashun (同花顺) Data Center, with a specific URL and return type. Though it lacks an explicit verb like 'get' or 'fetch', the resource and scope are unambiguous, and the name differentiates it from related IPO tools like stock_ipo_ths.

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?

Usage is implied by the data name and description: the agent can infer it is for IPO beneficiary stock data from 10jqka. However, there is no explicit guidance on when to use this tool versus sibling tools, nor any mention of exclusions or alternatives.

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