stock_gddh_em

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds no behavioral context beyond the fact that it returns a pandas DataFrame. It does not mention what the DataFrame contains (e.g., columns, date range), potential pagination, rate limits, or any notable edge cases. No contradiction with annotations, but minimal added value.

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, consisting of a title, URL, and return type. It is front-loaded with the title and has no fluff. However, it is under-specified, which is a completeness issue rather than a conciseness issue. The structure is logical but could include a brief sentence describing the action.

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 the tool's simplicity (no params, no output schema), the description still lacks essential context such as what specific fields or time periods the data covers, the format of the returned DataFrame, or any usage notes. The URL provides a reference but the description alone is not enough for an agent to understand the tool's full output. It is a minimal docstring that leaves out details an agent would typically need.

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 baseline is 4. The description does not need to explain parameter meanings since there are none. The URL provides a source reference, but that is not parameter-related. This is acceptable for a parameterless tool.

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 is essentially a label: '东方财富网-数据中心-股东大会' (East Money Network - Data Center - Shareholders' Meeting) followed by a URL and return type. It lacks an explicit verb like 'get' or 'fetch', and the resource is just a noun phrase. While the name and title imply it retrieves shareholder meeting data, the purpose is not clearly stated as an action. It does not distinguish itself from sibling tools beyond naming 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 provided on when to use this tool versus alternatives. It does not mention any prerequisites, scenarios, or exclusions. The description is purely declarative with no context on how this fits into a data-retrieval workflow.

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