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Csi Stock Analyzer
by
evanslin99
· GitHub ↗
· v1.0.0
· MIT-0
337
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Install in OpenClaw
/install csi-stock-analyzer
Description
专业A股投资分析工具,支持实时行情获取、技术指标分析(MACD/KDJ/RSI/EMA)、 智能数据缓存、新闻舆情分析。适用于中证2000成分股及全市场股票分析。 使用场景: 1. 需要分析某只股票的买入/卖出时机 2. 需要获取股票的技术指标信号(金叉/死叉/超买/超卖) 3. 需要批量分析中证2000成分股...
README (SKILL.md)
CSI 股票分析器
专业A股投资分析工具,提供实时行情、技术分析、智能缓存和舆情监控。
核心功能
- 实时行情获取: 全A股实时数据
- 技术分析: MACD、KDJ、RSI、EMA四大指标
- 智能缓存: SQLite本地缓存,增量更新
- 交易信号: 自动识别金叉/死叉/超买/超卖
- 舆情分析: 新闻监控和情感分析
快速开始
from core.stock_analyzer import AdvancedStockAnalyzer
analyzer = AdvancedStockAnalyzer()
result = analyzer.comprehensive_analysis('000977', days=120)
print(f"评级: {result['recommendation']['overall']}")
print(f"建议: {result['recommendation']['action']}")
技术指标说明
MACD
- 金叉买入: DIF上穿DEA,MACD柱由负转正
- 死叉卖出: DIF下穿DEA,MACD柱由正转负
KDJ
- 超卖买入: J值\x3C0且回升,或K线上穿D线
- 超买卖出: J值>100且回落,或K线下穿D线
RSI
- 超卖买入: RSI\x3C30且回升
- 超买卖出: RSI>70且回落
EMA
- 多头排列: 价格>EMA20>EMA60
- 空头排列: 价格\x3CEMA20\x3CEMA60
项目结构
csi2000_analyzer/
├── core/
│ ├── data_fetcher.py
│ ├── data_cache.py
│ ├── stock_analyzer.py
│ ├── news_analyzer.py
│ └── database.py
├── data/cache/
├── config.yaml
└── main.py
免责声明
本工具提供的所有数据和分析结果仅供参考,不构成任何投资建议。投资者应独立判断,自负盈亏。
Usage Guidance
This package appears to implement the advertised stock-analysis features and will call an external news API (api.tavily.com) and optionally market-data services. Before installing: 1) Be aware you must supply a TAVILY_API_KEY (and optionally other market tokens) even though the registry metadata doesn't list it — check README/config.yaml and avoid entering sensitive or unrelated credentials. 2) Review requirements.txt and run in an isolated environment (virtualenv/container) because it installs network-capable libraries (requests, pandas, etc.). 3) Expect the skill to create ./data/cache and ./reports on disk; if you want no external network access, run with include_news=False or don't set the API key. 4) Verify the Tavily service and API key provider you trust; avoid providing high‑privilege secrets. 5) Because source and homepage are unknown, prefer running first in a sandbox, inspect requirements and the few request calls (api.tavily.com) in core/data_fetcher.py, and only then use it with real credentials.
Capability Analysis
Type: OpenClaw Skill
Name: csi-stock-analyzer
Version: 1.0.0
The csi-stock-analyzer skill bundle is a legitimate stock analysis tool designed for the A-share market. It includes modules for technical analysis (MACD, KDJ, RSI, EMA), financial report evaluation, and news sentiment analysis using the Tavily API and web scraping from reputable sources like Eastmoney and Baidu. The code logic is transparent, lacks obfuscation, and does not exhibit signs of data exfiltration, unauthorized execution, or prompt injection. While some data fetching methods currently use simulated data or basic scraping (fetch_news.py), the behavior is consistent with the stated purpose of providing investment insights.
Capability Assessment
Purpose & Capability
Code implements real-time/news/technical/financial analysis consistent with the skill description. It uses a news API (api.tavily.com) and placeholders for market-data providers (tushare/akshare). However the registry metadata declares no required env vars/credentials while the code and README expect TAVILY_API_KEY (and optionally TUSHARE_TOKEN/AKSHARE_KEY). That mismatch is unexpected.
Instruction Scope
SKILL.md and README show normal usage (call AdvancedStockAnalyzer, run scripts/analyze_stock.py). Runtime instructions and code do not request unrelated system files or broad data collection. They do create/read local cache and write reports under ./data/cache and ./reports. The missing explicit instruction in SKILL.md about required API keys (TAVILY_API_KEY) is a scope/documentation gap.
Install Mechanism
No install spec in registry; this is an instruction+code package. Dependencies are standard (requests, pandas, numpy) referenced in requirements.txt and README recommends pip install -r requirements.txt. There are no downloads from untrusted URLs or archive extraction steps in the manifest.
Credentials
The code reads TAVILY_API_KEY via os.getenv and config.yaml references ${TAVILY_API_KEY}; it also mentions optional market-data tokens (TUSHARE_TOKEN, AKSHARE_KEY). Requesting a single news API key is proportionate to the stated functionality, but the registry declared no required env vars — the absence of declared credentials in metadata is an inconsistency that could mislead users. No unrelated secrets (e.g., AWS keys) are requested.
Persistence & Privilege
Skill is not always-enabled and does not request elevated platform privileges. It writes local cache and report files in relative paths (./data/cache, ./reports) which is expected for this application. It does not modify other skills or global agent settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install csi-stock-analyzer - After installation, invoke the skill by name or use
/csi-stock-analyzer - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
CSI Stock Analyzer 1.0.0 初始发布
- 提供专业A股实时行情查询与分析
- 支持MACD、KDJ、RSI、EMA等多种技术指标
- 自动识别交易信号(金叉/死叉/超买/超卖)
- 集成智能数据缓存,避免重复获取历史数据
- 实现中证2000及全A股的批量分析能力
- 支持股票相关舆情新闻监控与情感分析
Metadata
Frequently Asked Questions
What is Csi Stock Analyzer?
专业A股投资分析工具,支持实时行情获取、技术指标分析(MACD/KDJ/RSI/EMA)、 智能数据缓存、新闻舆情分析。适用于中证2000成分股及全市场股票分析。 使用场景: 1. 需要分析某只股票的买入/卖出时机 2. 需要获取股票的技术指标信号(金叉/死叉/超买/超卖) 3. 需要批量分析中证2000成分股... It is an AI Agent Skill for Claude Code / OpenClaw, with 337 downloads so far.
How do I install Csi Stock Analyzer?
Run "/install csi-stock-analyzer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Csi Stock Analyzer free?
Yes, Csi Stock Analyzer is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Csi Stock Analyzer support?
Csi Stock Analyzer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Csi Stock Analyzer?
It is built and maintained by evanslin99 (@evanslin99); the current version is v1.0.0.
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