What makes All-Market Financial Data Hub notable?

23.7K downloads. Trust evidence available

How should All-Market Financial Data Hub be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

All-Market Financial Data Hub

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 -

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

24k

Updated

Oct 9, 2026

Version

1.0.12

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 23.7K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 23.7K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.12release · observed Jun 5, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s172qfps754dhtdynwv0gwshes83mtd4:mx-finance-data

Setup 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.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-financial-ai-analyst-mx-finance-data/snapshot"

Documentation

CLAWHUB

41,546 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

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.

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