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 ZhuLinsen · Codex Skill · ★ 176
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is alphaevo safe to install? View the security audit →
🧬 AlphaEvo An Open-Source Self-Evolving Stock Strategy Research Agent Watch strategies get diagnosed, mutated, re-tested, and pruned like research assets Overview · Core Capabilities · Quick Start · Architecture · Validation · CLI English | 中文 ✨ Overview AlphaEvo is a self-evolving stock strategy research agent. It turns a readable YAML strategy into a research loop: backtest, diagnose failure, propose a controlled mutation, re-test the new version, and keep the full evidence trail.
| Stars | 176 |
| Forks | 71 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 63.1882971871734/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-03 |
| Created | 2026-03-31 |
| Platforms | docker, python |
| Est. Tokens | ~18k |
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🤖 A 股与港股 AI 研究智能体：行情、技术分析、新闻热点、交易信号、持仓管理与 Agent 问答一站式完成。
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alphaevo is An Self-Evolving Stock Strategy Research Agent 策略回测和自我进化. It is categorized as a Codex Skill with 176 GitHub stars.
alphaevo is primarily written in Python. It covers topics such as agent, evolution, finance.
You can find installation instructions and usage details in the alphaevo GitHub repository at github.com/ZhuLinsen/alphaevo. The project has 176 stars and 71 forks, indicating an active community.
alphaevo is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to alphaevo on Agent Skills Hub include TradingAgents-AShare, TradingAgents-MCPmode, hhxg-top-hhxg-python. 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: