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kevynf

AKBridge MCP Server

by kevynf

stock_individual_spot_xq

Read-onlyIdempotent

Fetch current stock quote from Xueqiu for an individual security by symbol, covering A-shares, ETFs, indices, and US stocks/indices with optional token.

Instructions

雪球-行情中心-个股 https://xueqiu.com/S/SH600000 :param symbol: 证券代码,可以是 A 股代码,A 股场内基金代码,A 股指数,美股代码,美股指数 :type symbol: str :param token: 雪球财经的 xq_a_token :type token: Optional[str] :param timeout: choice of None or a positive float number :type timeout: Optional[float] :return: 证券最新行情 :rtype: pandas.DataFrame :raises APIError: 雪球接口需要有效登录态时抛出

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenNo
symbolNoSH600000
timeoutNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, but the description adds genuine value beyond them: it discloses the :raises APIError condition when a valid Xueqiu login state is required, and explains the token is an xq_a_token. It does not describe rate limits or return format richness, but the auth caveat is the important behavior here.

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?

Front-loaded with the tool's Chinese name and an example URL, which is good, but the sphinx-style :param/:type/:return/:raises block is boilerplate that repeats field names. It is acceptable but not tight.

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

Completeness4/5

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

For a no-output-schema, 3-param read tool the description covers input semantics, the return type (pandas.DataFrame of latest quote) and the auth-failure mode. The main omission is guidance on choosing this source versus the many sibling spot/quote 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 coverage is 0%, so the description must carry the parameter burden and largely does: symbol is documented as accepting A-share codes, A-share ETF codes, A-share indices, US codes and US indices; token as the xq_a_token; timeout as None or a positive float. Only the default symbol value's meaning is left implicit.

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?

Names the source and resource (雪球-行情中心-个股) and states the output is 证券最新行情 for a single security, with a concrete example URL. It does not differentiate itself from the many sibling quote tools (e.g. stock_zh_a_spot_em, stock_individual_basic_info_xq), but the verb+resource is unambiguous.

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 never says when to pick this over an alternative quote source such as stock_zh_a_spot_em or stock_hk_spot_em, nor any prerequisites other than the token param. Usage is only implied by the title ('行情中心-个股').

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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