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liqiongyu

Xueqiu MCP

by liqiongyu

watch_stock

Retrieve detailed information about a specific watchlist from Xueqiu stock market data by providing the watchlist ID.

Instructions

获取用户自选列表详情

Args:
    pid: 自选列表ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pidYes

Implementation Reference

  • main.py:265-273 (handler)
    The handler function for the 'watch_stock' tool. It is decorated with @mcp.tool() which registers it in the MCP server. The function takes a pid (self-selected list ID), calls ball.watch_stock(pid) to fetch the data, processes it with process_data (which handles timestamp conversion), and returns the result as a dict.
    @mcp.tool()
    def watch_stock(pid: int) -> dict:
        """获取用户自选列表详情
        
        Args:
            pid: 自选列表ID
        """
        result = ball.watch_stock(pid)
        return process_data(result)
  • main.py:34-61 (helper)
    Helper function used by watch_stock (and all tools) to process the raw data from pysnowball, 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 helper recursively called by process_data to convert timestamp fields 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?

No annotations are provided, so the description carries the full burden. It mentions retrieving details but doesn't disclose behavioral traits such as whether it's a read-only operation, authentication requirements, rate limits, error conditions, or what format the details are returned in. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 concise and front-loaded with the main purpose in the first line. The additional parameter explanation is brief and directly relevant. There's no unnecessary verbosity, though it could benefit from more structured formatting.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what '详情' (details) includes, potential return values, or error handling. For a tool with no structured metadata, more context is needed to fully understand its operation and results.

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 adds minimal semantics: it states 'pid: 自选列表ID' (pid: watchlist ID), which clarifies that 'pid' refers to a watchlist identifier. However, with 0% schema description coverage and only 1 parameter, this provides basic but insufficient context. It doesn't explain valid ranges, examples, or how to obtain the ID, leaving room for improvement.

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: '获取用户自选列表详情' (Get user watchlist details). It specifies the verb '获取' (get) and resource '自选列表详情' (watchlist details). However, it doesn't explicitly differentiate from sibling tools like 'watch_list' or 'suggest_stock', which might have related functionality.

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, or comparisons to sibling tools like 'watch_list' or 'suggest_stock'. It only states what the tool does without indicating 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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