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Xpersona Agent
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 q... Skill: All-Market Financial Data Hub Owner: financial-ai-analyst Summary: 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 q... Tags: Ashare:1.0.4, financial:1.0.4, latest:1.0.12, quant:1.0.4, risk:1.0.4, stock:1.0.4, trade:1.0.4 Version history: v1.0.12 | 2026-06-05T11:29:40.664Z | user mx-finance-data 1.0.12 -
clawhub skill install s172qfps754dhtdynwv0gwshes83mtd4:mx-finance-dataOverall rank
#62
Adoption
23.7K downloads
Trust
Unknown
Freshness
Oct 9, 2026
Freshness
Last checked Oct 9, 2026
Best For
All-Market Financial Data Hub is best for general automation workflows where OpenClaw compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, CLAWHUB, runtime-metrics, public facts pack
Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.
Overview
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 q... Skill: All-Market Financial Data Hub Owner: financial-ai-analyst Summary: 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 q... Tags: Ashare:1.0.4, financial:1.0.4, latest:1.0.12, quant:1.0.4, risk:1.0.4, stock:1.0.4, trade:1.0.4 Version history: v1.0.12 | 2026-06-05T11:29:40.664Z | user mx-finance-data 1.0.12 - Capability contract not published. No trust telemetry is available yet. 23.7K downloads reported by the source. Last updated 10/9/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Oct 9, 2026
Vendor
Clawhub
Artifacts
0
Benchmarks
0
Last release
1.0.12
Install & run
clawhub skill install s172qfps754dhtdynwv0gwshes83mtd4:mx-finance-dataSetup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.
Public facts
Vendor
Clawhub
Protocol compatibility
OpenClaw
Latest release
1.0.12
Adoption signal
23.7K downloads
Handshake status
UNKNOWN
Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.
Captured outputs
Extracted files
3
Examples
6
Snippets
0
Languages
Unknown
bash
# macOS 添加到 ~/.zshrc,Linux 添加到 ~/.bashrc export EM_API_KEY="your_api_key_here"
bash
source ~/.zshrc
bash
source ~/.bashrc
bash
pip3 install httpx pandas openpyxl --user
bash
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何" --indicators "近期走势"bash
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)"SKILL.md
---
name: mx-finance-data
description: 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.
metadata:
{
"openclaw": {
"requires": {
"env":["EM_API_KEY"]
},
"install": [
{
"id": "pip-deps",
"kind": "python",
"package": "httpx pandas openpyxl",
"label": "Install Python dependencies"
}
]
}
}
---
# 金融数据查询
## 密钥来源与安全说明
- 本技能仅使用一个环境变量:`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。
- 在提供密钥前,请先确认密钥来源、可用范围、有效期及是否支持重置/撤销。
- 禁止在代码、提示词、日志或输出文件中硬编码/明文暴露密钥。
## 功能范围
### 1. 支持查询的对象范围
* 股票(A 股、港股、美股)
* 板块、指数、股东
* 企业发行人、债券、非上市公司
* 股票市场、基金市场、债券市场
### 2. 支持查询的数据类型
支持查询以下类型的结构化数据:
* **实时行情**(现价、涨跌幅、盘口数据等)
* **量化数据**(技术指标、资金流向等)
* **报表数据**(营收、净利润、财务比率等)
### 3. 查询方式与处理逻辑
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:
* **识别实体数 ≤ 5**:直接查数
* **识别实体数 > 5**:批量查数,最多处理识别结果中的前 **500** 个有效实体,如需大于500个实体,可分批多次调用
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`:
* 只填指标和时间范围等除实体外所有有效信息,不含实体名称等修饰语。
* 多个指标用用户原话拼接,如 `市盈率(动)和总市值`、`涨跌幅`、`营收、毛利、净利`。
* **不要在 `--indicators` 里重复写实体**。
* **尽量用用户原话表述,不要二次改写**。
> **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"`
### 4. 输出结果
Skill 执行后会输出两个文件:
- **Excel(.xlsx)**:多 sheet 结构化数据表,每个实体/指标组合对应一个 sheet
- **Markdown(.md)**:与 Excel 内容一致的 Markdown 表格,按 sheet 分二级标题
------
## 前提条件
### 1. 注册东方财富妙想账号
访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。
### 2. 配置 Token
```bash
# 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:**
```bash
source ~/.zshrc
```
**Linux:**
```bash
source ~/.bashrc
```
### 3. 安装依赖
```bash
pip3 install httpx pandas openpyxl --user
```
## 快速开始
在工作目录下执行:
```bash
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:
```bash
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|
------
### 输出示例
**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_meta.json
{
"ownerId": "kn7b4ptpdag877t9kmq8axyja182taab",
"slug": "mx-finance-data",
"version": "1.0.12",
"publishedAt": 1780658980664
}skill-card.md
## Description: Queries Eastmoney financial data from natural-language requests across A-shares, Hong Kong and US equities, ETFs, funds, bonds, indices, sectors, shareholders, issuers, and companies, returning structured Excel and Markdown results for investment and market analysis. This skill is ready for commercial/non-commercial use. ## Publisher: [financial-ai-analyst](https://clawhub.ai/user/financial-ai-analyst) ### License/Terms of Use: MIT-0 ## Use Case: Developers, analysts, and agents use this skill to fetch market quotes, financial indicators, company information, valuation data, and financial tables from natural-language finance questions. It supports research workflows such as investment analysis, market monitoring, trade review, sector analysis, credit review, financial statement review, and asset allocation. ### Deployment Geography for Use: Global ## Known Risks and Mitigations: Risk: An undocumented API endpoint override can expose EM_API_KEY if invoked with an untrusted URL. Mitigation: Use the documented CLI path, avoid custom API endpoint parameters, and keep the key revocable. Risk: The skill depends on a user-provided Eastmoney API key and third-party API workflow. Mitigation: Install only when the Eastmoney workflow is trusted, protect the EM_API_KEY value, and run in an isolated Python environment with reviewed dependency versions. ## Reference(s): - [ClawHub Skill Page](https://clawhub.ai/financial-ai-analyst/skills/mx-finance-data) - [Eastmoney Miaoxiang Claw Service](https://ai.eastmoney.com/mxClaw) ## Skill Output: **Output Type(s):** [Files, Markdown, Shell commands, Configuration instructions] **Output Format:** [CLI status text plus Excel workbooks and Markdown tables] **Output Parameters:** [1D] **Other Properties Related to Output:** [Requires EM_API_KEY and writes results under miaoxiang/mx_finance_data; multi-entity queries process up to 500 recognized entities per run.] ## Skill Version(s): 1.0.12 (source: release evidence) ## Ethical Considerations: Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
Editorial read
Docs source
CLAWHUB
Editorial quality
ready
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 q... Skill: All-Market Financial Data Hub Owner: financial-ai-analyst Summary: 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 q... Tags: Ashare:1.0.4, financial:1.0.4, latest:1.0.12, quant:1.0.4, risk:1.0.4, stock:1.0.4, trade:1.0.4 Version history: v1.0.12 | 2026-06-05T11:29:40.664Z | user mx-finance-data 1.0.12 -
Skill: All-Market Financial Data Hub
Owner: financial-ai-analyst
Summary: 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 q...
Tags: Ashare:1.0.4, financial:1.0.4, latest:1.0.12, quant:1.0.4, risk:1.0.4, stock:1.0.4, trade:1.0.4
Version history:
v1.0.12 | 2026-06-05T11:29:40.664Z | user
mx-finance-data 1.0.12
v1.0.11 | 2026-04-17T11:19:12.067Z | user
Publish 1.0.11
v1.0.10 | 2026-04-03T09:56:45.881Z | user
v1.0.9 | 2026-03-27T10:21:12.908Z | user
v1.0.8 | 2026-03-23T10:05:57.818Z | user
No code changes detected in this version.
v1.0.7 | 2026-03-20T15:15:58.729Z | auto
mx-finance-data 1.0.7
v1.0.6 | 2026-03-20T11:36:07.345Z | user
mx-finance-data 1.0.6
v1.0.5 | 2026-03-20T10:41:48.367Z | auto
v1.0.4 | 2026-03-18T08:31:42.682Z | user
v1.0.3 | 2026-03-17T09:58:36.167Z | user
No changes detected for version 1.0.3.
v1.0.2 | 2026-03-16T11:34:46.944Z | user
v1.0.1 | 2026-03-14T06:47:52.584Z | user
.txt description file.v1.0.0 | 2026-03-13T09:10:19.827Z | user
MX_FinData 1.0.0
Archive index:
Archive v1.0.12: 4 files, 14672 bytes
Files: scripts/get_data.py (34751b), skill-card.md (2285b), SKILL.md (6307b), _meta.json (135b)
File v1.0.12:SKILL.md
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
File v1.0.12:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.12", "publishedAt": 1780658980664 }
File v1.0.12:skill-card.md
Queries Eastmoney financial data from natural-language requests across A-shares, Hong Kong and US equities, ETFs, funds, bonds, indices, sectors, shareholders, issuers, and companies, returning structured Excel and Markdown results for investment and market analysis.
This skill is ready for commercial/non-commercial use.
MIT-0
Developers, analysts, and agents use this skill to fetch market quotes, financial indicators, company information, valuation data, and financial tables from natural-language finance questions. It supports research workflows such as investment analysis, market monitoring, trade review, sector analysis, credit review, financial statement review, and asset allocation.
Global
Risk: An undocumented API endpoint override can expose EM_API_KEY if invoked with an untrusted URL.
Mitigation: Use the documented CLI path, avoid custom API endpoint parameters, and keep the key revocable.
Risk: The skill depends on a user-provided Eastmoney API key and third-party API workflow.
Mitigation: Install only when the Eastmoney workflow is trusted, protect the EM_API_KEY value, and run in an isolated Python environment with reviewed dependency versions.
Output Type(s): [Files, Markdown, Shell commands, Configuration instructions]
Output Format: [CLI status text plus Excel workbooks and Markdown tables]
Output Parameters: [1D]
Other Properties Related to Output: [Requires EM_API_KEY and writes results under miaoxiang/mx_finance_data; multi-entity queries process up to 500 recognized entities per run.]
1.0.12 (source: release evidence)
Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
Archive v1.0.11: 4 files, 11802 bytes
Files: scripts/get_data.py (24569b), skill-card.md (2755b), SKILL.md (4968b), _meta.json (135b)
File v1.0.11:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 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
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.11:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.11", "publishedAt": 1776424752067 }
File v1.0.11:skill-card.md
Natural-language financial data query skill for A-shares, Hong Kong and US stocks, funds, bonds, indexes, issuers, company information, valuation metrics, financial reports, and market data using Eastmoney Miaoxiang data services. <br>
This skill is ready for commercial/non-commercial use. <br>
financial-ai-analyst <br>
MIT-0 <br>
Financial analysts, investors, researchers, and agents use this skill to retrieve structured market, company, fund, bond, valuation, and financial-statement data from natural-language questions. It is suited to investment research, trading review, market monitoring, industry analysis, credit research, financial reporting review, and asset allocation workflows. <br>
Global <br>
Risk: Financial queries are sent to Eastmoney, which may expose confidential holdings, strategy, or research topics. <br> Mitigation: Use the skill only when Eastmoney is approved for the submitted data, and avoid confidential holdings or proprietary research queries unless policy permits them. <br> Risk: The skill requires EM_API_KEY, a sensitive credential. <br> Mitigation: Use a revocable key stored in the environment, rotate or revoke it when needed, and avoid hard-coding it in prompts, code, logs, or shared files. <br> Risk: The skill installs Python packages and writes local XLSX and TXT files. <br> Mitigation: Install dependencies in a controlled virtual environment and review generated files before sharing or using them in downstream workflows. <br>
Output Type(s): [Text, Files, Shell commands, Configuration, Guidance] <br> Output Format: [Console text plus generated XLSX and TXT result files] <br> Output Parameters: [1D] <br> Other Properties Related to Output: [Writes local result files under miaoxiang/mx_finance_data and requires EM_API_KEY.] <br>
1.0.11 (source: server release metadata) <br>
Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>
Archive v1.0.10: 3 files, 10426 bytes
Files: scripts/get_data.py (24569b), SKILL.md (4968b), _meta.json (135b)
File v1.0.10:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 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
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.10:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.10", "publishedAt": 1775210205881 }
Archive v1.0.9: 3 files, 10495 bytes
Files: scripts/get_data.py (25193b), SKILL.md (5141b), _meta.json (134b)
File v1.0.9:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 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
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.9:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.9", "publishedAt": 1774606872908 }
Archive v1.0.8: 3 files, 10521 bytes
Files: scripts/get_data.py (25131b), SKILL.md (5241b), _meta.json (134b)
File v1.0.8:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 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
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.8:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.8", "publishedAt": 1774260357818 }
Archive v1.0.7: 3 files, 10484 bytes
Files: scripts/get_data.py (24745b), SKILL.md (4971b), _meta.json (134b)
File v1.0.7:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。
# 添加到 ~/.zshrc
export EM_API_KEY="your_api_key_here"
然后执行:
source ~/.zshrc
pip3 install httpx pandas openpyxl --user
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.7:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.7", "publishedAt": 1774019758729 }
Archive v1.0.6: 3 files, 10471 bytes
Files: scripts/get_data.py (25131b), SKILL.md (5114b), _meta.json (134b)
File v1.0.6:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。
# 添加到 ~/.zshrc
export EM_API_KEY="your_api_key_here"
然后执行:
source ~/.zshrc
pip3 install httpx pandas openpyxl --user
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.6:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.6", "publishedAt": 1774006567345 }
Archive v1.0.5: 3 files, 10397 bytes
Files: scripts/get_data.py (24509b), SKILL.md (4971b), _meta.json (134b)
File v1.0.5:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。
# 添加到 ~/.zshrc
export EM_API_KEY="your_api_key_here"
然后执行:
source ~/.zshrc
pip3 install httpx pandas openpyxl --user
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.5:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.5", "publishedAt": 1774003308367 }
Archive v1.0.4: 3 files, 9930 bytes
Files: scripts/get_data.py (22850b), SKILL.md (4971b), _meta.json (134b)
File v1.0.4:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。
# 添加到 ~/.zshrc
export EM_API_KEY="your_api_key_here"
然后执行:
source ~/.zshrc
pip3 install httpx pandas openpyxl --user
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18.xlsx
描述: /path/to/miaoxiang/mx_finance_data/mx_finance_data_9535fe18_description.txt
行数: 42
| 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>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.4:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.4", "publishedAt": 1773822702682 }
Archive v1.0.3: 3 files, 9725 bytes
Files: scripts/get_data.py (22825b), SKILL.md (4671b), _meta.json (134b)
File v1.0.3:SKILL.md
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:
支持多实体、多指标、多时间范围的组合查询。受后端接口限制,单次查询必须遵循以下配额:
示例: “查询 A、B、C、D、E、F 六只股票的营收” -> 仅返回前五只。
Skill 执行后会输出以下文件:
xlsx 文件,用于承载结构化查询结果txt 文件,用于描述查询内容、结果含义及必要说明访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。
# 添加到 ~/.zshrc
export EM_API_KEY="your_api_key_here"
然后执行:
source ~/.zshrc
pip3 install httpx pandas openpyxl --user
python3 {baseDir}/scripts/get_data.py --query "贵州茅台近期走势如何"
xlsx: /path/to/miaoxiang/MX_FinData/MX_FinData_9535fe18.xlsx
描述: /path/to/miaoxiang/MX_FinData/MX_FinData_9535fe18_description.txt
行数: 42
| 文件 | 说明 |
| --- | --- |
| MX_FinData_<查询id>.xlsx | 结构化数据表,包含请求的实体与指标 |
| MX_FinData_<查询id>_description.txt | 包含查询逻辑说明、字段含义及配额截断提示 |
File v1.0.3:_meta.json
{ "ownerId": "kn7b4ptpdag877t9kmq8axyja182taab", "slug": "mx-finance-data", "version": "1.0.3", "publishedAt": 1773741516167 }
Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.
Machine interfaces
Contract coverage
Status
missing
Auth
None
Streaming
No
Data region
Unspecified
Protocol support
Requires: none
Forbidden: none
Guardrails
Operational confidence: low
curl -s "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/contract"
curl -s "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/trust"
Operational fit
Trust signals
Handshake
UNKNOWN
Confidence
unknown
Attempts 30d
unknown
Fallback rate
unknown
Runtime metrics
Observed P50
unknown
Observed P95
unknown
Rate limit
unknown
Estimated cost
unknown
Do not use if
Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.
Contract JSON
{
"contractStatus": "missing",
"authModes": [],
"requires": [],
"forbidden": [],
"supportsMcp": false,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": null,
"outputSchemaRef": null,
"dataRegion": null,
"contractUpdatedAt": null,
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/snapshot",
"contractUrl": "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/contract",
"trustUrl": "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/trust"
},
"curlExamples": [
"curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/snapshot\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/contract\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "CLAWHUB",
"generatedAt": "2026-10-09T03:45:39.052Z"
}
},
"retryPolicy": {
"maxAttempts": 3,
"backoffMs": [
500,
1500,
3500
],
"retryableConditions": [
"HTTP_429",
"HTTP_503",
"NETWORK_TIMEOUT"
]
}
}Trust JSON
{
"status": "unavailable",
"handshakeStatus": "UNKNOWN",
"verificationFreshnessHours": null,
"reputationScore": null,
"p95LatencyMs": null,
"successRate30d": null,
"fallbackRate": null,
"attempts30d": null,
"trustUpdatedAt": null,
"trustConfidence": "unknown",
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Capability Matrix
{
"rows": [
{
"key": "OPENCLEW",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
}
],
"flattenedTokens": "protocol:OPENCLEW|unknown|profile"
}Facts JSON
[
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Clawhub",
"href": "https://clawhub.ai/financial-ai-analyst/skills/mx-finance-data",
"sourceUrl": "https://clawhub.ai/financial-ai-analyst/skills/mx-finance-data",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-10-09T01:36:15.101Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/contract",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-10-09T01:36:15.101Z",
"isPublic": true
},
{
"factKey": "traction",
"category": "adoption",
"label": "Adoption signal",
"value": "23.7K downloads",
"href": "https://clawhub.ai/financial-ai-analyst/mx-finance-data",
"sourceUrl": "https://clawhub.ai/financial-ai-analyst/mx-finance-data",
"sourceType": "profile",
"confidence": "medium",
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{
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]Change Events JSON
[
{
"eventType": "release",
"title": "Release 1.0.12",
"description": "mx-finance-data 1.0.12 - Added new files: a compiled Python script and a sample Excel file. - Removed the skill-card.md file. - SKILL.md: Cleaned up documentation by removing environment setup, security, and registration details; condensed and restructured the feature description for clarity.",
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]Sponsored
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