stock_a_below_net_asset_statistics

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 the data source URL and the return type (pandas.DataFrame), which is useful. However, it does not describe any additional behavioral aspects such as data granularity, time range, or potential delays.

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 title, URL, param, and return sections. The phrase '破净股统计历史走势' appears twice (as the heading and the return description), which is mildly redundant, but the document is otherwise free of filler.

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 read-only tool with one parameter and no output schema, the description supplies the necessary invocation details: parameter choices, return type, and source URL. The rich annotations cover safety, so the overall context is sufficient for an agent to call the tool correctly, though it lacks guidance on when to prefer this tool over siblings.

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 defines 'symbol' as a string with a default, but the description enriches this by enumerating valid choices: 全部A股, 沪深300, 上证50, 中证500. This directly compensates for the 0% schema description coverage, providing essential information for correct invocation.

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: historical statistics of stocks trading below net asset value. The phrase '破净股统计历史走势' is a noun phrase rather than an explicit verb, but the meaning is unambiguous and the URL supports it. It does not explicitly differentiate from sibling tools like stock_a_all_pb, but the scope is clear enough.

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 vs alternatives. It does not state prerequisites, typical use cases, or scenarios where another tool would be more appropriate. Given the large list of sibling tools, this omission is a notable gap.

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