stock_zt_pool_zbgc_em

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds the exact source URL and the return type (pandas DataFrame), but does not disclose potential limitations such as valid date formats or that non-trading days may produce empty results. It does not contradict 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 follows a docstring structure with purpose, URL, parameter, and return type. It is concise with no filler, though the Chinese docstring style may not be optimally front-loaded for an English-speaking agent, and it starts with a resource name rather than an imperative.

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 one-parameter, read-only tool with no output schema, the description provides the essential data source, parameter, and return type. However, it lacks detail on the DataFrame structure and date format, and does not clarify how this tool relates to sibling limit-up pool tools, making it minimally adequate but not 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 schema has a single date parameter with type string and default, but no schema description. The description repeats '交易日' (trading day) and type str, adding only the concept of a trading day without specifying the date format (e.g., YYYYMMDD) or any constraints, leaving the agent to infer from the default value.

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 identifies the exact data source (Eastmoney limit-up board center) and the specific pool ('炸板股池' broken board pool) with a URL, and states it returns a pandas DataFrame. However, it lacks an explicit verb like 'get' or 'fetch' and does not differentiate from sibling tools such as stock_zt_pool_em, so it is clear but not fully distinguishing.

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 a date parameter indicating that it queries data for a specific trading day, but offers no guidance on when to use this tool versus sibling limit-up pool tools like stock_zt_pool_em or stock_zt_pool_strong_em. No exclusions or alternatives are mentioned.

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