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liqiongyu

Xueqiu MCP

by liqiongyu

indicator

Retrieve annual and quarterly financial performance reports for specific stocks from the Xueqiu stock market data service.

Instructions

按年度、季度获取业绩报表数据

Args:
    stock_code: 股票代码
    is_annals: 只获取年报,默认为1
    count: 返回数据数量,默认5条

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stock_codeNoSZ000002
is_annalsNo
countNo

Implementation Reference

  • main.py:141-152 (handler)
    The handler function for the 'indicator' MCP tool. It is registered via @mcp.tool() decorator. Fetches performance indicator data from pysnowball.ball.indicator with parameters for stock code, annual/quarterly reports, and count, then processes the data with timestamps conversion.
    @mcp.tool()
    def indicator(stock_code: str="SZ000002", is_annals: int = 1, count: int = 5) -> dict:
        """按年度、季度获取业绩报表数据
        
        Args:
            stock_code: 股票代码
            is_annals: 只获取年报,默认为1
            count: 返回数据数量,默认5条
        """
        result = ball.indicator(symbol=stock_code, is_annals=is_annals, count=count)
        return process_data(result)
  • main.py:141-141 (registration)
    The @mcp.tool() decorator registers the subsequent indicator function as an MCP tool named 'indicator' (by function name).
    @mcp.tool()
  • The function signature and docstring define the input schema (parameters with types, defaults, descriptions) and output type (dict).
    def indicator(stock_code: str="SZ000002", is_annals: int = 1, count: int = 5) -> dict:
        """按年度、季度获取业绩报表数据
        
        Args:
            stock_code: 股票代码
            is_annals: 只获取年报,默认为1
            count: 返回数据数量,默认5条
        """
  • main.py:34-61 (helper)
    Shared helper function used by the indicator tool (and others) to process response data, including converting timestamps to readable datetime strings.
    def process_data(data, process_config=None):
        """
        通用数据处理函数,可扩展添加各种数据处理操作
        
        Args:
            data: 原始数据
            process_config: 处理配置字典,用于指定要执行的处理操作
                例如: {'convert_timestamps': True, 'other_process': params}
        
        Returns:
            处理后的数据
        """
        if process_config is None:
            # 默认配置
            process_config = {
                'convert_timestamps': True
            }
        
        # 如果开启了时间戳转换
        if process_config.get('convert_timestamps', True):
            data = convert_timestamps(data)
        
        # 在这里可以添加更多的数据处理逻辑
        # 例如:
        # if 'format_numbers' in process_config:
        #     data = format_numbers(data, **process_config['format_numbers'])
        
        return data
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool retrieves data but doesn't specify whether this is a read-only operation, what format the data returns, whether there are rate limits, authentication requirements, or any side effects. The description is minimal and lacks important behavioral context for a data retrieval tool.

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 appropriately concise with a clear purpose statement followed by parameter explanations. The two-sentence structure is efficient, though the parameter explanations could be better integrated. There's no wasted text, and the information is front-loaded with the core purpose first.

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?

For a 3-parameter tool with no annotations, 0% schema description coverage, and no output schema, the description is insufficient. It doesn't explain what 'performance report data' actually contains, what format it returns, or provide examples. The tool appears to retrieve financial data but lacks critical context about the data structure, potential limitations, or error conditions.

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?

With 0% schema description coverage, the description provides basic parameter explanations in Chinese: stock_code (股票代码), is_annals (只获取年报,默认为1 - annual reports only, default 1), and count (返回数据数量,默认5条 - number of returned data items, default 5). This adds meaningful context beyond the schema's bare field names, but doesn't fully compensate for the complete lack of schema descriptions, especially for the ambiguous 'is_annals' parameter.

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 tool's purpose as '按年度、季度获取业绩报表数据' (Get performance report data by year/quarter), which specifies both the verb (获取/get) and resource (业绩报表数据/performance report data). It distinguishes from siblings like 'balance' or 'income' by focusing on performance reports rather than specific financial statements. However, it doesn't explicitly differentiate from 'report' which might be similar.

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. With many sibling tools like 'balance', 'income', 'cash_flow', and 'report', there's no indication of when this performance report tool is appropriate versus those other financial data tools. The description only states what it does, not when to choose it.

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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