bank_fjcf_table_detail

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds behavioral details such as returning a pandas.DataFrame ordered from first to last page and that 'page' controls how many initial pages are fetched. It does not mention potential pitfalls like pagination limits or data freshness, but given the strong annotations, a 3 is appropriate.

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 as a docstring with a clear purpose line followed by parameter and return documentation. Every line adds value, such as the cross-reference to the total page function. It is not overly verbose, though the opening line is essentially the same as the annotation title, which is slightly redundant. Overall, it is appropriately sized and front-loaded.

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?

Given the tool's moderate complexity, the description is sufficiently complete: it specifies the return type (pandas.DataFrame), the ordering of results, and links to a companion function for total pages. It lacks a breakdown of DataFrame columns, but there is no output schema to supplement this, and the nature of the data (administrative penalty details) is implied by the tool name and title. The read-only and idempotent annotations also cover operational context.

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 description explains all three parameters beyond the schema: 'page' indicates fetching the first N pages, 'begin' is the starting page, and 'item' lists explicit choices ('机关', '本级', '分局本级'). This is especially valuable because the schema has no per-parameter descriptions (coverage 0%). The only minor gap is the exact interaction between 'begin' and 'page' (e.g., does 'page' count from 'begin' or from page 1), which prevents a 5.

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 data from a specific administrative penalty information disclosure table (行政处罚信息公开表) on the CBIRC branch page. The verb '获取' (get) plus the specific resource path ('首页-政务信息-行政处罚-银保监分局本级') makes the purpose unambiguous. It is easily distinguished from sibling tools, which cover unrelated domains like funds, futures, and macro indicators.

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 implies usage for fetching this table's data and provides useful context: use 'ak.bank_fjcf_total_page()' to obtain total pages for the 'page' parameter. However, it does not explicitly state when to prefer this tool over alternatives or provide exclusion conditions, so it falls short of a 4. The guidance is embedded in parameter descriptions rather than a dedicated usage section.

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