stock_yysj_em

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive nature. The description adds that it returns a pandas DataFrame and points to a data source URL, but does not disclose potential errors, rate limits, or data quirks. This adds some context beyond annotations but not substantial.

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 compact docstring with a clear structure: title, source URL, parameter definitions, and return type. It is not overly verbose, but the URL and type info are arguably necessary. It front-loads the purpose.

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 (two parameters, no output schema), the description covers purpose, parameters, and return type. It does not detail column names or edge cases, but annotations cover safety and idempotency. Overall, it is sufficiently 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?

The input schema has no descriptions for parameters, but the description compensates by enumerating valid values for 'symbol' and providing example date formats and a start date. This gives the agent clear semantics for both parameters.

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 states the tool retrieves scheduled disclosure times from East Money's data center, with a specific URL and return type. However, it does not explicitly differentiate it from sibling tools like stock_yjbb_em or stock_yjkb_em, so it lacks sibling differentiation.

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 parameter documentation but does not state when to choose this tool over alternatives, nor does it offer any context on use cases or exclusions. It only describes what the tool does, not when to use it.

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