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liqiongyu

Xueqiu MCP

by liqiongyu

index_perf_7

Retrieve the performance data of a stock index over the past 7 days to track recent market trends and investment returns.

Instructions

获取指数最近7天收益数据

Args:
    index_code: 指数代码

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
index_codeNoSZ000002

Implementation Reference

  • main.py:343-351 (handler)
    The primary handler function for the MCP tool 'index_perf_7'. It is registered via the @mcp.tool() decorator, fetches 7-day index performance data from pysnowball (ball.index_perf_7), processes timestamps, and returns the result as a dict. Includes input schema via type hints and docstring.
    @mcp.tool()
    def index_perf_7(index_code: str="SZ000002") -> dict:
        """获取指数最近7天收益数据
        
        Args:
            index_code: 指数代码
        """
        result = ball.index_perf_7(index_code)
        return process_data(result)
  • main.py:34-61 (helper)
    Supporting helper function called by index_perf_7 to process the raw data, primarily converting Unix timestamps to human-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)
    Recursive utility helper to convert timestamp fields (including _date suffixes) in nested data structures to formatted datetime strings, invoked by process_data.
    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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it indicates this is a read operation ('获取' - get), it doesn't describe what the tool returns (e.g., data format, structure, or specific metrics), whether there are rate limits, authentication requirements, or any error conditions. For a data retrieval tool with zero annotation coverage, this leaves significant behavioral gaps.

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 two sentences: one stating the purpose and another listing the parameter. It's front-loaded with the core functionality. While efficient, the parameter documentation could be slightly more informative given the lack of schema descriptions.

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 the tool's complexity (data retrieval with time-based filtering), absence of annotations, and no output schema, the description is incomplete. It doesn't explain what '收益数据' (performance data) entails, the return format, or how the 7-day period is calculated. For a tool that likely returns financial metrics, more context is needed for effective use.

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?

The description explicitly documents the single parameter 'index_code' and provides a brief explanation ('指数代码' - index code). However, with 0% schema description coverage, the schema only provides a default value and title without semantic context. The description adds basic meaning but doesn't elaborate on parameter format, valid values, or examples beyond what's implied by the default 'SZ000002'.

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: '获取指数最近7天收益数据' (Get index recent 7-day performance data). It specifies the verb '获取' (get) and resource '指数收益数据' (index performance data) with a time scope of '最近7天' (recent 7 days). However, it doesn't explicitly differentiate from sibling tools like 'index_perf_30' or 'index_perf_90', which appear to serve similar functions with different timeframes.

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. It doesn't mention sibling tools like 'index_perf_30' or 'index_perf_90' that likely provide similar data for different time periods, nor does it specify any prerequisites, exclusions, or contextual constraints for usage.

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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