stock_zcfz_bj_em

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safe read-only nature is clear. The description adds context about the data source (East Money data center) and return type (DataFrame), which is useful. However, it does not disclose behaviors like data range limits, pagination, or potential differences in data availability across dates.

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 title line, URL, and parameter/return documentation. It repeats the title that also appears in annotations, but it is still concise and well-structured. The information is front-loaded, with the main purpose stated first.

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 has one parameter and no output schema, so the description must carry more weight. It states the return is a pandas DataFrame and the parameter options, but it omits details about what columns the DataFrame contains (e.g., total assets, liabilities) and does not clarify that 'bj' signifies Beijing Stock Exchange. This leaves some ambiguity for an agent selecting the tool.

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 only lists 'date' with a default but no description, so the description must compensate. It does so by specifying the date format (YYYYMMDD), giving example values like 20200331 and 20200630, and noting the valid range starts from 20100331. This adds meaningful semantics beyond the bare 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 states the tool retrieves a balance sheet (资产负债表) from East Money's data center for annual/quarterly reports. The verb is implied ('get' or 'retrieve') and the resource is specific. However, it does not explicitly distinguish itself from the similarly named sibling tool stock_zcfz_em, beyond the 'bj' suffix in the tool name which suggests Beijing Stock Exchange but is never mentioned in the description.

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?

No guidance is provided on when to use this tool versus alternatives. The description only documents the parameter format and return type. It does not specify that this tool is for Beijing Stock Exchange balance sheets or contrast it with related tools like stock_zcfz_em.

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