stock_dxsyl_em

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

The annotations already declare read-only, idempotent, and non-destructive behavior, so the description's job is lighter. It adds the return type (pandas.DataFrame) and the source URL, which are useful context beyond annotations. However, it does not mention any network dependency or scraping behavior, which is acceptable given the 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 brief and front-loaded with the data domain, followed by the source URL and return type. All lines contribute meaningful information, though the URL on a separate line and the docstring-style annotations add minor clutter.

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 data retrieval tool, the description covers the essential aspects: what data (IPO subscription yield), where from (Eastmoney URL), and what is returned (pandas.DataFrame). It lacks detailed column descriptions, but given the simplicity and annotations, it is sufficient.

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 description does not need to explain parameter semantics. The baseline of 4 applies because there are no parameter fields to describe.

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 resource as Eastmoney's new stock subscription yield data (打新收益率) and includes a specific URL, which distinguishes it from other IPO-related tools like stock_ipo_benefit_ths. Although it lacks an explicit verb like 'retrieve', the intent is clear from the context.

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 provided about when to use this tool versus alternative IPO data sources such as stock_ipo_declare_em or stock_ipo_benefit_ths. The tool is implicitly for fetching this specific dataset, but there is no explicit when/when-not guidance.

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