stock_ipo_declare_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds a source URL and return type (pandas.DataFrame), which is useful but does not reveal behavioral traits like data coverage, update frequency, or volume. 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 short and front-loaded with source and resource, but it redundantly repeats '东方财富网-数据中心-新股数据' and '首发申报企业信息' multiple times. The URL and return type documentation are useful, but the repetition means not every sentence earns its place.

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 no output schema, the description should detail what the returned DataFrame contains, but it only names the category '首发申报企业信息' without listing any columns, fields, or examples. There is no explanation of how data is organized or filtered, leaving an agent without enough context to fully 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 and the schema has no properties, so there is nothing to explain. The description appropriately focuses on the returned entity type, and with no parameters, the baseline 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 names the resource: 东方财富网数据中心新股数据-首发申报企业信息, and provides a URL to the exact data page. It indicates the tool returns IPO declaration enterprise information as a pandas DataFrame. However, it lacks an explicit action verb like 'Get' or 'Return', and its differentiation from sibling ipo tools is only implicit through the specific data category.

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 the many sibling stock_ipo_* tools, nor does it state any exclusions or prerequisites. The agent must infer usage solely from the name and description, which is insufficient for choosing among alternatives.

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