Claude Skill

ALAGENT-HKU/x2strategy

x2strategy 是一个开源 Claude Skill，可从量化金融研究论文中提取结构化策略规范，使 AI 代理能够解析并标准化交易策略。

概览

Stars150
Forks26
语言Python
最后更新2026-05-25
最近同步2026-06-25
前往 GitHub

仓库信息

拥有者ALAGENT-HKU
仓库x2strategy
完整名称ALAGENT-HKU/x2strategy
Repo ID1,192,629,876
GitHub 地址https://github.com/ALAGENT-HKU/x2strategy

安装这个 Skill

npx clawhub@latest install x2strategy
GitHub

Registry 信息

类型openclaw_skill
质量分85/100
验证状态readme_parsed
最近验证2026-06-25
平台
ClaudeOpenClawCodex
能力
pdfmemorysearchimageterminalworkflow
识别文件
README.mdSKILL.mddocsexamplespyproject.tomlrequirements.txttests
配置键
DEEPSEEK_API_KEYOPENROUTER_API_KEYOPENAI_API_KEYANTHROPIC_API_KEY
安装方式
  • npx clawhub@latest install x2strategy
  • git clone https://github.com/ALAGENT-HKU/x2strategy.git ~/.copilot/skills/x2strategy
  • git clone https://github.com/ALAGENT-HKU/x2strategy.git ~/.claude/skills/x2strategy
  • git clone https://github.com/ALAGENT-HKU/x2strategy.git .github/skills/x2strategy
  • pip install -e ".[codegen,agent,docx,dev]"

项目简介

x2strategy 是一个开源的 Claude Skill，旨在从量化金融研究论文中提取结构化的策略规范。它使 GitHub Copilot 和 Claude Code 等 AI 代理能够解析学术论文并输出标准化的交易策略定义，从而弥合金融研究与算法实现之间的鸿沟。

英文描述

Extract structured strategy specifications from quantitative finance research papers — Agent Skill for GitHub Copilot & Claude Code

要点

  • 从量化金融论文中提取结构化策略规范
  • 输出标准化的交易策略定义
  • 作为 Agent Skill 集成到 GitHub Copilot 和 Claude Code
  • 使用 Python 构建，实现高效的论文解析
  • 开源且由社区驱动开发

使用场景

  • 从研究论文中自动提取策略用于回测
  • 使 AI 代理能够阅读和解释金融文献
  • 标准化交易策略以实现跨平台部署
  • 通过结构化输出加速量化研究工作流程

README 摘要

<div align="center"> <img src="assets/alagent_logo.png" alt="ALAGENT Logo" width="120"> # X2Strategy **Any Research Input → Strategy Spec → Executable Code → Backtest → Diagnosis** [![Python 3.11+](https://img.shields.io/badge/python-3.11%2B-blue?logo=python&logoColor=white)](https://python.org) [![License: Apache-2.0](https://img.shields.io/badge/license-Apache--2.0-green.svg)](LICENSE) [![Agent Skills](https://img.shields.io/badge/Agent_Skills-compatible-blueviolet?logo=visualstudiocode)](https://agentskills.io/) [![Tests](https://img.shields.io/badge/tests-180_passed-brightgreen)]() [![LiteLLM](https://img.shields.io/badge/LLM-any_provider-orange?logo=openai)](https://docs.litellm.ai/docs/providers) [Getting Started](#-getting-started) · [How It Works](#-how-it-works) · [Examples](#-examples) · [Docs](#-documentation) · [简体中文](README_CN.md) --- *Turn quantitative finance research — papers, drafts, reports, or strategy ideas — into validated, executable trading strategies. Automatically.* </div> ## Highlights - **🔬 Multi-Format Input** — PDF papers, Markdown drafts, DOCX reports, plain text. Auto-detected. - **🧠 5-Layer LLM Extraction** — Multi-strategy detection → indicators → signal logic → execution plan → risk controls. - **🧾 Grounded Extraction Quality** — Optional instruction/customization/clarification context, retrieved repair-time operator-pitfall checks, canonical `portfolio_weights`, and structured `needs_human_review` flags. - **✅ Verified Code Generation** — AST validation + Backtrader structural checks + indicator registry, not just "generate and hope". - **📊 Automated Backtesting** — Execute, extract metrics, and diagnose against paper-reported performance. - **🤖 Agent-Native** — Works as an [Agent Skill](https://agentskills.io/) (`/x2strategy

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拥有者: ALAGENT-HKU语言: Python

数据来自 GitHub，同步时间：2026-06-25