stock_qbzf_em

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is clear. The description adds the source URL and return type, which is useful context, but does not disclose behavioral traits such as network dependency, data update frequency, or potential columns. This is acceptable given the low bar set by 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 short and to the point, containing only the data source, URL, and return type. It is concise, but the format is a raw docstring fragment rather than structured prose, which slightly reduces clarity.

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?

The tool is simple with no parameters and no output schema. The description provides the key facts: what data is returned, the source URL, and the return type. However, it omits details like the DataFrame columns, time range, or update frequency, which would help an agent understand the data fully.

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 there is nothing to document. According to the rubric, 0 parameters gives a baseline of 4, and the schema coverage is trivially 100%. No additional semantic explanation is needed.

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 data source and content: '东方财富网-数据中心-新股数据-增发-全部增发' (Eastmoney Data Center - New Stock Data - Additional Issuance - All Additional Issuance) and specifies the return type as pandas.DataFrame. It is a specific resource, though it lacks an explicit verb like 'get' or 'list' and does not differentiate from sibling 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?

No guidance is provided about when to use this tool vs alternatives. It does not mention exclusions, prerequisites, or alternative tools, leaving the agent to infer usage solely from the description.

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