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. Full audit →
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 | 78 |
| Forks | 3 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 54/100 |
| Last Updated | 2026-06-16 |
| Created | 2026-04-22 |
| Platforms | python |
| Est. Tokens | ~16k |
awesome-llm-paper-wiki 🇺🇸 English | 🇨🇳 简体中文 一个由 LLM agent 驱动的结构化、可持续演进的文献综述系统。它可以基于本地 Markdown 文献文件，完成整理、标签、分析，并生成可用于论文写作和投稿决策的综述报告。 🎯 仓库能做什么？ awesome-llm-paper-wiki 管理一个本地 Markdown 文献库，并让你的 LLM agent 处理重复性的文献工作： 💡 为什么要做这个项目？ 这个项目适合下面几类高频科研场景： 用 Gemini、ChatGPT、Qwen、DeepSeek 等 LLM 做文献调研，但结果不够稳定。 通用 deep research 容易受访问范围、抓取深度和上下文限制影响。这个项目把本地 Markdown 文献库作为稳定信息源，把“网络搜索”作为补充信息源，让 Agent...
Looking for a awesome-llm-paper-wiki alternative? If you're comparing awesome-llm-paper-wiki with other ai tool tools, these 3 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Skip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights
Skill to talk to Claude about your projects over the phone
.NET MAUI skills for GitHub Copilot and Claude Code
Explore other popular ai tool tools:
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: