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kevynf

AKBridge MCP Server

by kevynf

stock_hk_daily

Read-onlyIdempotent

Fetch historical daily price data for Hong Kong stocks by symbol, with options for unadjusted, forward-adjusted, or adjustment factor results for analysis.

Instructions

新浪财经-港股-个股的历史行情数据 https://stock.finance.sina.com.cn/hkstock/quotes/02912.html :param symbol: 可以使用 ak.stock_hk_spot() 获取 :type symbol: str :param adjust: "": 返回未复权的数据 ; qfq: 返回前复权后的数据;qfq-factor: 返回前复权因子和调整; :type adjust: str :return: 指定 adjust 的数据 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adjustNo
symbolNo00981

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds the data source, return type, and adjust-value behavior, but omits important behavior such as the default date range, frequency, pagination, or rate limits.

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 purpose is front-loaded, followed by a source URL and parameter documentation. The docstring-style type lines and return type add some redundancy but remain compact and relevant.

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 description covers the core purpose, parameter semantics, and return type, and annotations cover safety. However, with no output schema and no date range or row-level return behavior described, the definition leaves meaningful gaps for an agent selecting among many similar HK stock data tools.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry parameter meaning. It explains the adjust parameter values well (unadjusted, qfq, qfq-factor) and explains where to obtain a valid symbol, though it does not document the symbol format or default values beyond the schema.

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 states a specific resource: Sina Finance historical daily quote data for individual Hong Kong stocks. It is clear what data the tool returns, but it does not distinguish itself from sibling tools such as stock_hk_hist or stock_hk_spot.

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 only tells the user that the symbol can be obtained via ak.stock_hk_spot(). It gives no guidance on when to use this tool instead of alternatives like stock_hk_hist or stock_hk_spot, and no when-not conditions are provided.

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

Deploy Server

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