A股港股股票分析

v1.0.0

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。

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for zh40/a-h-stock-analysis.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "A股港股股票分析" (zh40/a-h-stock-analysis) from ClawHub.
Skill page: https://clawhub.ai/zh40/a-h-stock-analysis
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install a-h-stock-analysis

ClawHub CLI

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npx clawhub@latest install a-h-stock-analysis
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Purpose & Capability
Name/description (stock analysis using Tushare/AKShare) match the included scripts and requirements. The scripts implement basic info, historical data, fundamental and technical analysis as described.
Instruction Scope
Runtime instructions are limited to installing Python packages, setting TUSHARE_TOKEN (optional), and running the provided scripts. They do not ask to read unrelated files or send data to unknown endpoints. Minor issue: SKILL.md's installation example omits akshare even though the code falls back to AKShare; also the package list in requirements.txt includes akshare but SKILL.md's pip line does not.
Install Mechanism
This is instruction-only with bundled Python scripts and a requirements.txt — no remote downloads or custom install hooks. Risk is typical for pip-installed packages; user should install from official package index. No install spec exists in the registry metadata.
Credentials
The code optionally reads TUSHARE_TOKEN from the environment to access Tushare; that is proportionate to the stated purpose. Metadata, however, lists no required env vars while SKILL.md instructs setting TUSHARE_TOKEN — a documentation mismatch but not a sign of excessive privilege.
Persistence & Privilege
Skill does not request persistent or elevated platform privileges (always is false), does not modify other skills, and does not write global agent config. It only reads an optional Tushare token from the environment and performs normal network calls to the data providers.
Assessment
This skill appears to do what it says: fetch stock data from Tushare (if you provide TUSHARE_TOKEN) and fall back to AKShare. Before installing/running: (1) install dependencies in a virtual environment and include akshare (requirements.txt lists akshare but the README pip example omits it); (2) only set TUSHARE_TOKEN if you trust the environment — the token is used to call the official Tushare API; (3) review/verify pip package sources (install from PyPI or your trusted mirror); (4) if you run this in a shared environment, avoid exposing sensitive tokens—the scripts make network calls to Tushare/AKShare and print results but do not contain obfuscated or exfiltration code. The main issues are documentation/metadata mismatches (missing env var declaration and incomplete install instructions), not malicious behavior.

Like a lobster shell, security has layers — review code before you run it.

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145downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

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

# 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

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