stock_gsrl_gsdt_em

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

No annotations are provided, so the description must fully disclose behavior. It does not indicate whether the operation is read-only, has side effects, requires authentication, or any constraints. The minimal description fails to convey expected behavioral traits.

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 concise at one sentence, but it is vague and does not front-load critical information. While no word is wasted, the sentence does not earn its place due to lack of 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?

Given no output schema and the ambiguous description, the tool lacks sufficient context for an agent to understand what data is returned. It does not mention response structure, data scope, or any other completeness cues.

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?

With 100% schema description coverage, the schema already documents the 'date' parameter and its format. The description does not add additional meaning beyond what is in the schema, so it meets the baseline score of 3.

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 '获取股市日历-公司动态数据' vaguely states it retrieves stock market calendar company dynamic data, but '公司动态数据' is ambiguous and does not clearly specify what data is returned. Compared to sibling tools like 'realtime_quote' or 'stock_zh_a_hist', the purpose is less clear and lacks distinction.

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 explicit guidance is provided on when to use this tool versus sibling tools. The description does not mention context, prerequisites, or alternatives, leaving the agent without criteria for selection.

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