by modelscope · Agent Tool · ★ 472
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 472 |
| Forks | 64 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 53/100 |
| Open Issues | 12 |
| Last Updated | 2026-11-07 |
| Created | 2026-06-12 |
| Platforms | python |
| Est. Tokens | ~16k |
🔬 Awesome Vibe Research 面向 AI 辅助科研的开放共建仓库 收集和沉淀科研全流程中的 agents、skills、workflows、tools 与最佳实践 🇨🇳 中文版 | 🇬🇧 English 🧪 全流程 • 🔭 方向扫描 • 📚 文献研究 • 🧩 方法设计 • ⚗️ 实验执行 • 📊 可视化 • ✍️ 写作 • 📦 复现发布 • 📡 传播 • 🤝 贡献 我们关注能在科研工作中反复复用、能被同行验证、能逐步演化、表现最优的 AI 辅助能力。 本仓库从「与 Agent 共事做研究」系列沙龙出发，希望把 speaker 的实践经验、观众的使用反馈、开源项目与可复用流程沉淀成一个社区可维护的知识库。 🗺️ 科研流程地图 下表是我们对科研生命周期的 9 阶段拆分。每个阶段列出了"典型问题"和"可沉淀的 AI...
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: