When to use it
The official description does not include a separate “Use when”. Per the spec, agents activate this skill when the task matches keywords in that description.
Skills ZICQ category:Documents mx-finance-data OpenClaw
Based on the Eastern Wealth Database, which supports the search of financial data in natural languages and covers a wide range of assets, including real-time situations, company information, valuations, financial statements, etc., that can be used for investment research, trade re-entry, market monitoring, industry analysis, credit research, financial audit, asset allocation, etc., and for adaptation institutions and individuals. Returns a result that contains xlsx with a Markdown file. It involves L1/L2 data, companies and valuations.
Official URL:ClawHub
Intro in this page language first. The official description stays in its original wording; we do not rewrite SKILL.md.
The official description does not include a separate “Use when”. Per the spec, agents activate this skill when the task matches keywords in that description.
Per Agent Skills progressive disclosure: name and description load at startup (~100 tokens); the full SKILL.md body loads when the skill activates; scripts/, references/, and assets/ load only as needed. This file's sections: 金融数据查询; 密钥来源与安全说明; 功能范围; 1. 支持查询的对象范围; 2. 支持查询的数据类型; 3. 查询方式与处理逻辑.
File analysis: besides SKILL.md, the body references scripts/get_data.py. Those resources load on demand.
基于东方财富数据库,支持自然语言查询金融数据,覆盖A港美、基金、债券等多种资产,含实时行情、公司信息、估值、财务报表等,可用于投资研究、交易复盘、市场监控、行业分析、信用研究、财报审计、资产配置等场景,适配机构与个人多元需求。返回结果包含 xlsx 与 Markdown 文件。Natural language query for financial data across all markets, including A-shares, ETFs, bonds, Hong Kong and US stocks, and funds. It provides L1/L2 data, financial indicators, company profiles and valuation metrics. Ideal for investment research, strategy backtesting, market monitoring and industry analysis. It meets the needs of diverse institutions and individuals.
金融数据查询密钥来源与安全说明功能范围1. 支持查询的对象范围2. 支持查询的数据类型3. 查询方式与处理逻辑4. 输出结果前提条件1. 注册东方财富妙想账号2. 配置 TokenmacOS 添加到 ~/.zshrc,Linux 添加到 ~/.bashrc3. 安装依赖
Source category:ClawHub Investment
Market sources:ClawHub
namemx-finance-datadescriptionscripts/get_data.pyThese paths are extracted from the text. Check the upstream package to verify the files exist.
Invocation syntax and available tools depend on your Agent client. Client integration guide ↗
Choose the target agent and installation scope, keep referenced package files, then verify the skill appears in the client's catalog.
This skill references supporting files. Retrieve the complete directory from the source; copying SKILL.md alone may leave missing dependencies.
Copy these instructions to a compatible agent and confirm the target directory matches your client.
Install the agent skill "mx-finance-data" into my project. The full SKILL.md and official description are at https://zicq.com/en/skills/skl-44400180165b3568-Mx-Finance-Data.html Save it as .cursor/skills/mx-finance-data/SKILL.md or .claude/skills/mx-finance-data/SKILL.md and keep the frontmatter name and description exactly as-is. This skill also ships scripts/, references/, or assets/ — fetch the whole folder from https://clawhub.ai/skills/mx-finance-data instead of creating only a SKILL.md.
No unambiguous GitHub package URL is recorded. Follow the original source's installer instructions.
EM_API_KEY。EM_API_KEY 由东方财富妙想服务(https://ai.eastmoney.com/mxClaw)签发,用于其接口鉴权。支持查询以下类型的结构化数据:
统一使用 --query 传入自然语言问句(包含实体与指标),并使用 --indicators 传入从问句中提取的金融指标等关键信息。Skill 会先对 query 做实体识别,再按识别结果选择查数路径:
注意:当用户问句中只包含代词,需结合上下文或者提供文件读取所有实体名称,一并输入query。
--indicators 参数说明调用本 Skill 前,需根据 --query 从用户问句中提取需要查询的金融指标(或指标组),填入 --indicators:
市盈率(动)和总市值、涨跌幅、营收、毛利、净利。--indicators 里重复写实体。示例
用户问「查询贵州茅台、五粮液近一年营收」
→--query "查询贵州茅台、五粮液近一年营收" --indicators "近一年营收"
用户问「这批股票的涨跌幅是多少」或列出 6 只以上股票
→--query "查询 A、B、C、D、E、F 六只股票的涨跌幅、pe、市值" --indicators "涨跌幅、pe、市值"
Skill 执行后会输出两个文件:
访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。
# macOS 添加到 ~/.zshrc,Linux 添加到 ~/.bashrc
export EM_API_KEY="your_api_key_here"
然后根据系统执行对应的命令:
macOS:
source ~/.zshrc
Linux:
source ~/.bashrc
pip3 install httpx pandas openpyxl --user
在工作目录下执行:
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何" --indicators "近期走势"
多实体示例:
python3 {baseDir}/scripts/get_data.py --query "查询贵州茅台、五粮液、宁德时代、比亚迪、隆基绿能、中芯国际的市盈率(动)" --indicators "市盈率(动)"
参数说明:
| 参数 | 必填 | 默认值 | 说明 |
| --- | --- | --- | --- |
| --query | 是 | - | 自然语言查询问句,需包含所有查询实体名称|
| --indicators | 是 | - | 从 query 中提取的金融指标、时间范围等关键信息|
直接查数:
识别实体数: 1
查数模式: 直接查数
返回实体数: 1
文件: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
Markdown: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.md
表格行数: 42
多实体查数:
识别实体数: 128
查数模式: 多实体
返回实体数: 128
文件: /path/to/miaoxiang/mx_finance_data/mx_finance_data_a1b2c3d4.xlsx
Markdown: /path/to/miaoxiang/mx_finance_data/mx_finance_data_a1b2c3d4.md
表格行数: 150
| 文件 | 说明 |
| --- | --- |
| mx_finance_data_<查询id>.xlsx | 结构化数据表,包含请求的实体与指标 |
| mx_finance_data_<查询id>.md | 与 Excel 内容一致的 Markdown 表格 |
错误:请设置 EM_API_KEY 环境变量
API_KEY。EM_API_KEY环境变量多实体查数报错:缺少 --indicators
--indicators,否则无法构造有效的查数问句。当前一次请求的数据量过大,部分数据可能会有缺失,请减少指标数量和查询日期范围
多实体查数最多处理识别结果中前 500 个有效实体
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