What makes A股港股股票分析 notable?

1.1K downloads. Trust evidence available

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A股港股股票分析

A股和港股股票数据分析工具，优先使用Tushare数据，Tushare不可用时自动回退到AKShare获取行情、财务指标，支持基本面分析和技术分析。 Skill: A股港股股票分析 Owner: zh40 Summary: A股和港股股票数据分析工具，优先使用Tushare数据，Tushare不可用时自动回退到AKShare获取行情、财务指标，支持基本面分析和技术分析。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-10T06:47:37.861Z | user A股和港股股票数据分析工具，支持Tushare/AKShare双数据源，提供基本面和技术面分析 Archive index: Archive v1.0.0: 10 files, 8521 bytes Files: references/tushare-api.md (1052b), requirements.txt (60b), scripts/fundamental_analysis.py (2312b), scripts/get_basic.py (59

OpenClaw

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Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

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 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.0.0release · observed Apr 10, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: medium.

clawhub skill install s17fc68hfr26dqgrqc26dfcb1584a7xm:a-h-stock-analysis

Python environment detected. Create a strict virtual environment (`python -m venv .venv`) before installing dependencies to prevent system-level package conflicts.
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
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-zh40-a-h-stock-analysis/snapshot"

Documentation

CLAWHUB

4,821 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: a-stock-analysis
description: A股和港股股票数据分析工具，优先使用Tushare数据，Tushare不可用时自动回退到AKShare获取行情、财务指标，支持基本面分析和技术分析。
---

# A股港股股票分析

基于Tushare + AKShare双数据源的A股和港股股票基本面、技术面分析。

- **优先使用Tushare**：如果配置了Tushare Token且能正常访问，用Tushare数据
- **自动回退AKShare**：Tushare不可用、没Token或请求失败时自动切AKShare公开数据源

## 前置准备

1. **推荐配置Tushare**：访问 https://tushare.pro/ 注册并获取Token，设置环境变量 `TUSHARE_TOKEN=你的token`
2. **AKShare不需要Token**：直接可用，不需要注册

## 功能

- 获取个股基本信息
- 获取历史行情数据
- 财务指标分析（Tushare优先）
- 技术指标计算（MA、MACD、RSI等）
- 支持A股（沪/深/北）和港股

## 使用

### 安装依赖

```bash
# 需要Python 3和tushare库
pip install tushare pandas numpy
```

### 获取股票基本信息

`scripts/get_basic.py --code <股票代码>`

股票代码规则：
- A股：直接使用6位代码 (e.g., 000001 平安银行)
- 港股：使用5位代码 (e.g., 00700 腾讯控股)

### 获取历史行情

`scripts/get_historical.py --code <股票代码> --start <YYYYMMDD> --end <YYYYMMDD>`

### 基本面分析

`scripts/fundamental_analysis.py --code <股票代码>`

## 参考

- [Tushare API文档](references/tushare-api.md) - 常用API说明

_meta.json

{
  "ownerId": "kn75egn5cw4cqebmz3etxa1fjh83404z",
  "slug": "a-h-stock-analysis",
  "version": "1.0.0",
  "publishedAt": 1775803657861
}

references/tushare-api.md

# Tushare API 常用接口

## 通用说明

- 所有接口需要初始化：
```python
import tushare as ts
pro = ts.pro_api(your_token)
```

## A股港股基础信息

### 股票列表
```python
# A股
data = pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date')

# 港股
data = pro.hk_basic()
```

## 日线行情
```python
# A股
df = pro.daily(ts_code=ts_code, start_date=start_date, end_date=end_date)

# 港股
df = pro.hk_daily(ts_code=ts_code, start_date=start_date, end_date=end_date)
```

## 财务指标
```python
# A股
df = pro.fina_indicator(ts_code=ts_code)

# 港股也可以通过此接口获取
```

## 每日指标（包含技术指标基础数据）
```python
df = pro.daily_basic(ts_code=ts_code, trade_date=trade_date)
```

## 代码转换规则

Tushare格式：`[代码].[交易所后缀]`
- 沪市A股：`XXXXXX.SH`
- 深市A股：`XXXXXX.SZ`
- 北交所A股：`XXXXXX.BJ`
- 港股：`XXXXXX.HK`

用户输入6位A股代码自动补全后缀，5位港股代码自动补全 `.HK`

skill-card.md

## Description:

A股和港股股票数据分析工具，优先使用Tushare数据，Tushare不可用时自动回退到AKShare获取行情、财务指标，支持基本面分析和技术分析。

This skill is ready for commercial/non-commercial use.

## Publisher:

[zh40](https://clawhub.ai/user/zh40)

### License/Terms of Use:

MIT-0

## Use Case:

External users, developers, and analysts use this skill to retrieve A-share and Hong Kong stock data, inspect company basics and financial indicators, and calculate common technical indicators with Tushare preferred and AKShare fallback.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The scripts contact Tushare or AKShare and may use a TUSHARE_TOKEN environment variable.

Mitigation: Install and run the skill in an isolated Python environment, set TUSHARE_TOKEN only when comfortable using Tushare, and expect outbound market-data requests.

Risk: Dependency version ranges may resolve to package versions that differ from those reviewed at release time.

Mitigation: Prefer a reviewed, pinned requirements file or lock file before production use.

Risk: Stock data, financial metrics, and technical indicators can be unavailable, delayed, or incomplete from either data source.

Mitigation: Validate important outputs against trusted market-data sources before relying on them for financial decisions.

## Reference(s):

- [Tushare API 常用接口](references/tushare-api.md)
- [Tushare](https://tushare.pro/)
- [ClawHub skill page](https://clawhub.ai/zh40/skills/a-h-stock-analysis)

## Skill Output:

**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Files]

**Output Format:** [Markdown guidance with inline shell commands, terminal tables, and optional CSV output]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Uses TUSHARE_TOKEN when configured; otherwise falls back to AKShare where available.]

## Skill Version(s):

1.0.0 (source: release metadata)

## 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.

requirements.txt

tushare>=1.2.73
akshare>=1.14.0
pandas>=1.3.0
numpy>=1.21.0

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