Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/fivif/OmniKBTaken from the project's README on GitHub. Check the security audit before running it.
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 | 55 |
| Forks | 8 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 60/100 |
| Last Updated | 2026-06-05 |
| Created | 2026-05-07 |
| Platforms | python |
| Est. Tokens | ~14k |
OmniKB 按场景划分的知识库问答系统 多源聚合 · 场景专属 Wiki · 一键发布 · 零嵌入开销 在线体验 · 测试报告 左：Wiki 知识图谱 ｜ 右：500 题大规模幻觉测试报告 中文 · English 什么是 OmniKB OmniKB 是一个按场景划分的知识库问答系统。核心思路： 导入知识源 — 上传文档、粘贴文本、抓取 URL 创建场景 — 每个场景绑定自己的知识源，配置专属 system prompt、UI 模板、API 密钥 一键发布 — 自动生成公开问答页（），嵌入官网或作为 Age
Looking for a OmniKB alternative? If you're comparing OmniKB 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: