A股自动选股系统 — 多种技术形态自动扫描,收盘后自动运行并推送飞书
$ npx skills add sngyai/Sequoia-XAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
A股自动选股系统 — 多种技术形态自动扫描,收盘后自动运行并推送飞书
$ npx skills add sngyai/Sequoia-XPython wrapper for TA-Lib (http://ta-lib.org/).
$ npx skills add TA-Lib/ta-lib-python30天掌握量化交易 (持续更新)
$ npx skills add Rockyzsu/stock天勤量化开发包, 期货量化, 实时行情/历史数据/实盘交易
$ npx skills add shinnytech/tqsdk-python开放式的缠论python实现框架,支持形态学/动力学买卖点分析计算,多级别K线联立,区间套策略,可视化绘图,多种数据接入,策略开发,交易系统对接;
$ npx skills add Vespa314/chan.py基于Python的开源量化交易平台开发框架
$ npx skills add vnpy/vnpystock股票.获取股票数据,计算股票指标,筹码分布,识别股票形态,综合选股,选股策略,股票验证回测,股票自动交易,支持PC及移动设备。
$ npx skills add myhhub/stockQUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
$ npx skills add yutiansut/QUANTAXISHikyuu Quant Framework 基于C++/Python的超高速开源量化交易研究框架,同时可基于策略部件进行资产重用,快速累积策略资产。
$ npx skills add fasiondog/hikyuu$ npx skills add refraction-ray/xalpha基于深度强化学习的开源自动因子工厂。
$ npx skills add imbue-bit/AlphaGPT[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
$ npx skills add UFund-Me/QbotTradingAgents: Multi-Agents LLM Financial Trading Framework
$ npx skills add TauricResearch/TradingAgentsFinancial data platform for analysts, quants and AI agents.
$ npx skills add OpenBB-finance/OpenBBFree, open source crypto trading bot
$ npx skills add freqtrade/freqtradeQlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
$ npx skills add microsoft/qlibHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Rqalpha if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.