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kevynf

AKBridge MCP Server

by kevynf

currency_boc_sina

Read-onlyIdempotent

Retrieves historical Bank of China RMB exchange rates for major currencies from Sina Finance, enabling querying by currency and date range.

Instructions

新浪财经-中行人民币牌价历史数据查询 https://biz.finance.sina.com.cn/forex/forex.php?startdate=2012-01-01&enddate=2021-06-14&money_code=EUR&type=0 :param symbol: choice of {'美元', '英镑', '欧元', '澳门元', '泰国铢', '菲律宾比索', '港币', '瑞士法郎', '新加坡元', '瑞典克朗', '丹麦克朗', '挪威克朗', '日元', '加拿大元', '澳大利亚元', '新西兰元', '韩国元'} :type symbol: str :param start_date: 开始交易日 :type start_date: str :param end_date: 结束交易日 :type end_date: str :return: 中行人民币牌价历史数据查询 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo美元
end_dateNo20231110
start_dateNo20230304
Behavior3/5

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 the data source and return type, but does not disclose rate limits, pagination, or column structure. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a compact docstring-style block with title, URL, parameters, and return type. It is front-loaded and efficient, though the long URL may be unnecessary for the agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple query tool with 3 parameters and no output schema, the description covers parameter meanings and return type. However, it lacks date format clarification, column-level return details, and usage context relative to sibling tools, leaving some gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description is the main source of parameter meaning. It explains symbol as a choice of currencies and start_date/end_date as trading days, and mentions the DataFrame return. However, it does not specify the expected date format clearly; the URL example uses dashes while schema defaults use compact digits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a historical data query for Bank of China RMB exchange rates via Sina Finance, with a specific URL and parameter list. It specifies the resource and action, but does not explicitly differentiate from sibling currency tools like currency_boc_safe or currency_history.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 only states what it does, not when it should be preferred over the many sibling currency/forex tools.

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

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