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kevynf

AKBridge MCP Server

by kevynf

stock_zh_a_hist

Read-onlyIdempotent

Fetch historical A-share stock prices from East Money, with daily, weekly, or monthly periods and optional price adjustment for accurate backtesting and analysis.

Instructions

东方财富网-行情首页-沪深京 A 股-每日行情 https://quote.eastmoney.com/concept/sh603777.html?from=classic :param symbol: 股票代码 :type symbol: str :param period: choice of {'daily', 'weekly', 'monthly'} :type period: str :param start_date: 开始日期 :type start_date: str :param end_date: 结束日期 :type end_date: str :param adjust: choice of {"qfq": "前复权", "hfq": "后复权", "": "不复权"} :type adjust: str :param timeout: choice of None or a positive float number :type timeout: float :return: 每日行情 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adjustNo
periodNodaily
symbolNo000001
timeoutNo
end_dateNo20500101
start_dateNo19700101
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds the data source (East Money) and return type (pandas.DataFrame), but does not disclose any additional behavioral details such as rate limits, pagination, or how adjust values affect data. It does not contradict annotations, so it scores at a baseline level for a read-only historical data tool.

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

Conciseness3/5

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

The description includes a URL that is not essential for an AI agent and the structure mixes a Chinese title, URL, and parameter docs in a single block. While the parameter docs are useful and clear, the overall presentation is not as concise or well-structured as it could be, with extraneous URL and redundant title information.

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?

The tool has 6 parameters and no output schema, so the description should explain the return format. It only states the return is '每日行情' (daily quotes) of type pandas.DataFrame, without detailing columns or data granularity. This is minimally sufficient but lacks the richness needed to fully understand the output and edge cases, especially given the large sibling set.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden for parameter documentation. It provides detailed docs for all six parameters, including choices for period and adjust, date semantics for start_date/end_date, and timeout as None or positive float. This fully compensates for the missing schema descriptions and gives an agent everything needed to invoke the tool correctly.

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 states the resource (East Money A-share daily quotes) and includes the URL source. The parameter list for period and adjust indicates it's a historical data retrieval tool. However, it lacks an explicit verb like 'fetch' or 'retrieve', and it does not differentiate itself from siblings like stock_zh_a_daily or stock_zh_a_hist_tx.

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?

No guidance is provided on when to use this tool versus alternatives. The description simply lists parameters and return type, with no mention of scenarios, prerequisites, or exclusions. The sibling tools offer similar functions (e.g., stock_zh_a_hist_min_em, stock_zh_a_daily), and this description does not help an agent choose among them.

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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