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kevynf

AKBridge MCP Server

by kevynf

stock_individual_info_em

Read-onlyIdempotent

Get individual stock information from Eastmoney by providing a stock symbol. Returns structured data on price, volume, and other market metrics for analysis.

Instructions

东方财富-个股-股票信息 https://quote.eastmoney.com/concept/sh603777.html?from=classic :param symbol: 股票代码 :type symbol: str :param timeout: choice of None or a positive float number :type timeout: float :return: 股票信息 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo603777
timeoutNo
Behavior3/5

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

With annotations declaring readOnlyHint=true, destructiveHint=false, and idempotentHint=true, the safety profile is covered. The description adds the return type (pandas.DataFrame) and the timeout parameter constraint, providing some context, but it does not describe output content, error behavior, or data source specifics.

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 compact and front-loaded with a title and URL. The docstring-like format is efficient, but the :param/:type lines are somewhat redundant with the schema and the overall layout is not optimized for an AI agent's quick scanning.

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

Completeness2/5

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

There is no output schema, and the description only says 'returns pandas.DataFrame'. It does not specify what fields or information are included, leaving the agent unable to predict the actual data. This is a significant gap for selecting among the many stock-information sibling 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 carries the burden. It explains 'symbol' as a stock code (股票代码) and clarifies that timeout is a positive float or None, which adds meaning beyond the JSON schema's bare type declarations. However, the timeout description is still a type constraint rather than its behavioral role.

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 the tool returns '股票信息' (stock information) for an individual stock from Eastmoney, with a sample URL. This is a clear purpose but not very specific about what 'stock information' includes, and it doesn't explicitly differentiate from sibling tools like stock_zh_a_spot_em or stock_individual_basic_info_xq.

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?

There is no guidance on when to use this tool versus alternatives. The description only provides parameter documentation and a URL; it does not mention intended scenarios, prerequisites, or why an agent should choose this over sibling 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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