stock_research_report_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the return type (pandas.DataFrame) and the source URL, providing some behavioral context. However, it does not disclose details like pagination, data volume, or potential rate limits, so it adds limited value beyond 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 a concise docstring with clear sections for source, parameter, and return, front-loaded with the title and URL. Every line earns its place, though the URL could be seen as extraneous. It is well-structured and appropriately sized, though not exceptionally compact.

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 (one optional parameter) and the description explains the source and return type, which is useful. However, with no output schema, it does not describe the DataFrame columns or what the research report data contains, leaving the agent guessing about the result structure. The absence of any mention of data range, filtering, or pagination makes it only minimally complete.

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 schema description coverage at 0%, the description carries the burden for parameter meaning. It documents ':param symbol: 个股代码' (individual stock code), which clarifies the purpose of the single parameter, and the schema's default '000001' suggests a 6-digit A-share code. Yet it omits format specifics (e.g., exchange prefix, applicable markets), leaving some ambiguity.

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 states the resource (东方财富网-数据中心-研究报告-个股研报 = East Money Data Center individual stock research report) and includes a URL, which clearly scopes it to a specific data source and type. However, it lacks an explicit verb like 'fetch' or 'return', though the docstring's ':return: 个股研报' implies retrieval, so it stops short of a fully specific verb+resource statement.

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?

The description provides no guidance on when to use this tool versus alternatives. It only describes the source and parameter, without mentioning any exclusions, competitor tools, or specific use cases. This leaves the agent to infer usage purely from the name and source.

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