stock_margin_ratio_pa

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds a source URL and parameter constraints (allowed symbol values) but does not disclose additional behavioral traits like rate limits, pagination, or data freshness. It does not contradict annotations; the query verb aligns with read-only.

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 front-loaded with the title as the first line, followed by a URL and docstring-style params. It includes a small redundancy: the return line repeats the title phrase '标的证券名单及保证金比例查询'. Overall, it is appropriately sized with minimal waste.

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 query with two optional, defaulted parameters, the description covers the purpose, parameters, return type (DataFrame), and data source URL. It does not have an output schema, but the description sufficiently explains what the tool returns. It is complete enough for an agent to invoke correctly.

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?

Schema description coverage is 0%, so the description must compensate. It does provide docstring-style meanings: symbol is limited to {'深市', '沪市', '北交所'} and date is '交易日期' (trading date). However, it fails to specify the date format (though the default '20260113' hints at it) and does not describe the return DataFrame columns in detail. This partial compensation merits a score of 3.

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's function: '融资融券-标的证券名单及保证金比例查询' (Margin trading - underlying securities list and margin ratio query). It specifies the resource (标的证券名单及保证金比例) and the action (查询), and distinguishes from sibling margin tools by covering three exchanges (深市/沪市/北交所) with a URL source. This matches a specific verb+resource pattern.

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 does not mention exclusions, prerequisites, or direct comparisons to sibling margin tools (e.g., stock_margin_sse). The usage context is only implied by the parameter choices, not explicitly stated.

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