Fetch monthly performance reports for securities firms from East Money's data center by month, returning structured data for analysis.
东方财富网-数据中心-特色数据-券商业绩月报 http://data.eastmoney.com/other/qsjy.html :param date: 数据月份，从 2010-06-01 开始，e.g.，需要 2011 年 7 月，则输入 2011-07-01 :type date: str :return: 券商业绩月报 :rtype: pandas.DataFrame
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | 20200731 |
Changes observed during successful MCP inspections.
v0.1.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, so the description earns credit for adding the return type (pandas.DataFrame), source URL, and the data start date (2010-06-01). It does not describe pagination or update frequency, but the added behavioral context is useful beyond 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 compact and front-loads the dataset identity, source, parameter guidance, and return type. The URL and docstring-style fields are structured and not wasteful, though slightly boilerplate.
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 single-parameter, read-only data retrieval tool with no output schema, the description covers the data source, parameter format, and return type adequately. It could mention output columns, but that is not required without an output schema.
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?
Schema coverage is 0% and the single date parameter is undocumented in the schema, but the description fully compensates by giving the format, the start date (2010-06-01), and a concrete example showing 2011-07-01 for July 2011. This is exactly what an agent needs to construct the call correctly.
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?
States a specific dataset: 东方财富网券商业绩月报, with a source URL, making the resource clear and distinguishable from macro or stock-list siblings. It lacks an explicit retrieval verb, but the data purpose is evident.
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?
Provides no when-to-use guidance, no when-not-to-use conditions, and does not name alternatives among the many sibling data tools. Only the date range is mentioned, which is parameter help rather than usage routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.