stock_zh_a_stop_em

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful context about the source (East Money page) and return type, but does not discuss data freshness, column structure, or potential network behavior.

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 concise, containing essential elements: source, content, and return type. It is appropriately sized for a no-parameter tool, though the first line simply mirrors the title, which is a slight redundancy.

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 simple list-fetch tool, the description identifies the exact data source and content, and the return type is clear. However, it omits usage guidance, differentiation from similar tools, and details about the DataFrame columns, which would be valuable given no 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?

The tool has zero parameters, so with 100% schema coverage, the description need not explain parameters. It does add value by stating the returned dataset (two networks and delisted stocks), providing meaning beyond the empty schema.

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 resource as '两网及退市' (two networks and delisted stocks) from East Money and specifies the return type as a pandas DataFrame. However, it lacks a direct verb like 'get' or 'list' and does not differentiate from sibling tools such as stock_zh_a_st_em or stock_staq_net_stop.

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?

There is no guidance on when to use this tool versus alternatives. The description only provides a source URL and return type, leaving the agent to infer its purpose among many similar stock list tools.

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