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liqiongyu

Xueqiu MCP

by liqiongyu

fund_trade_date

Check trading dates for specific funds to verify market availability before transactions using Xueqiu MCP's financial data.

Instructions

获取基金交易日期信息

Args:
    fund_code: 基金代码

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fund_codeNoSZ000002

Implementation Reference

  • main.py:475-483 (handler)
    The handler function for the 'fund_trade_date' tool. It is decorated with @mcp.tool() for registration and FastMCP integration. The function fetches fund trade date data using the pysnowball library (ball.fund_trade_date) and processes the result with process_data for timestamp conversion.
    @mcp.tool()
    def fund_trade_date(fund_code: str="SZ000002") -> dict:
        """获取基金交易日期信息
        
        Args:
            fund_code: 基金代码
        """
        result = ball.fund_trade_date(fund_code)
        return process_data(result)
  • main.py:34-61 (helper)
    Helper function used by the fund_trade_date handler (and all other tools) to process the raw data, primarily 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
  • main.py:14-31 (helper)
    Supporting utility called by process_data to recursively convert timestamp fields (including those ending with '_date') in the data to formatted datetime strings.
    def convert_timestamps(data):
        """递归地将数据中的所有 timestamp 转换为 datetime 字符串"""
        if isinstance(data, dict):
            for key, value in list(data.items()):
                if key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000000:  # 毫秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S')
                elif key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000:  # 秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S')
                elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000000:  # 毫秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S')
                elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000:  # 秒级时间戳
                    data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S')
                elif isinstance(value, (dict, list)):
                    data[key] = convert_timestamps(value)
        elif isinstance(data, list):
            for i, item in enumerate(data):
                data[i] = convert_timestamps(item)
        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 only states what information is retrieved without describing response format, error conditions, rate limits, authentication needs, or whether the data is real-time vs historical. For a tool with zero annotation coverage, this represents significant gaps in behavioral context.

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 brief with two sentences that directly address purpose and parameters. The structure is clear with purpose first followed by parameter documentation. No unnecessary information is included, though the formatting could be slightly improved for readability.

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?

Given no annotations, no output schema, and 0% schema description coverage, the description is incomplete for effective tool use. While it states the basic purpose and parameter, it lacks crucial information about return format, error handling, data freshness, and how this tool differs from similar sibling tools in the financial data context.

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?

The description explicitly documents the single parameter 'fund_code' with a brief explanation, though schema description coverage is 0%. Since there's only one parameter and the description provides its purpose, this adequately compensates for the lack of schema documentation. However, it doesn't provide format examples or validation rules beyond the basic explanation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states '获取基金交易日期信息' (Get fund trading date information), which provides a basic verb+resource combination. However, it's somewhat vague about what specific trading date information is retrieved (e.g., next trading day, historical schedule, settlement dates) and doesn't distinguish from sibling tools like 'fund_info' or 'fund_detail' that might also provide related data.

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 doesn't mention prerequisites, context for use, or compare it to sibling tools like 'fund_info' that might overlap in functionality. This leaves the agent without clear direction on appropriate usage scenarios.

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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