No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ALAGENT-HKU · Agent Tool · ★ 255
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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X2Strategy Any Research Input → Strategy Spec → Executable Code → Backtest → Diagnosis []() Getting Started · How It Works · Examples · Docs · 简体中文 Turn quantitative finance research — papers, drafts, reports, or strategy ideas — into validated, executable trading strategies. Automatically. 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 , and structured flags. ✅ Verified Code Gene
| Stars | 255 |
| Forks | 45 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 64.6802573847091/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-12 |
| Created | 2026-03-26 |
| Platforms | claude-code, python |
| Est. Tokens | ~13k |
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x2strategy is Extract structured strategy specifications from quantitative finance research papers — Agent Skill for GitHub Copilot & Claude Code. It is categorized as a Agent Tool with 255 GitHub stars.
x2strategy is primarily written in Python.
You can find installation instructions and usage details in the x2strategy GitHub repository at github.com/ALAGENT-HKU/x2strategy. The project has 255 stars and 45 forks, indicating an active community.
The top alternatives to x2strategy on Agent Skills Hub include awesome-android-agent-skills, agent-skills, claude-code-skill-factory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: