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

No annotations are provided, so the description must disclose behavioral traits. It discloses that the return is a JSON array with specific fields, which is useful. However, it does not mention whether filters are combined (AND), if at least one filter is required, if results are paginated or limited, or that it is a read-only operation. The behavioral info beyond the schema is minimal.

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 well-structured and concise: a short title, an Args list matching the schema, and a Returns section. It is front-loaded, easy to scan, and contains no unnecessary prose. The redundancy with the schema is acceptable and does not inflate length unnecessarily.

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 output schema covers return values, but the description lacks important contextual details for an AI agent. It does not state that all parameters are optional, how filters interact, or whether calling with no filters returns the entire universe of stocks (which could be a huge response). It also does not explain the distinction from sibling tools, leaving the agent without enough context to choose this tool confidently.

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 covers 100% of the parameters with descriptions, so the schema already documents parameter meaning. The description repeats the same parameter descriptions without adding extra semantics such as filter combination logic, default behavior, or value formatting beyond what is in the schema. Baseline of 3 applies.

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 tool as a stock list providing basic information, with a specific title '股票列表（基础信息）' and a Returns section defining the output fields. It is distinct from sibling tools like daily or fundamentals, although it does not explicitly name alternatives or state the scope (e.g., 'List all stocks matching filters').

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 lists filter parameters but does not state whether this should be used for querying basic stock metadata, whether it is the default for lookup, or what scenarios are better suited for other sibling tools. There is no explicit when-to-use or when-not-to-use guidance.

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