Skill comparison
Compare agent skills before installing.
Put high-signal skills side by side and inspect quality, adoption, freshness, install readiness, use-case fit, and warnings in one place.
Comparing 4 skills
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
Siyuan is the strongest overall pick here because it has a 100/100 readiness score and fits RAG and knowledge.
Strongest overall
Siyuan
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Siyuan
Best first install candidate based on install readiness and adoption.
Freshest repo
AIGC Interview Book
Most recent maintenance signal among this shortlist.
| Signal | AIGC Interview Book 【三年面试五年模拟】AIGC/LLM/AI Agent算法工程师面试秘籍。涵盖AIGC、LLM大模型、AI Agent、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、强化学习、大数据挖掘、具身智能、元宇宙、AGI等AI行业面试笔试干货经验与核心知识。 | AgentGuide https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习｜数据合成 | LazyLLM Easiest and laziest way for building multi-agent LLMs applications. | Siyuan A privacy-first, self-hosted, fully open source personal knowledge management software, written in typescript and golang. |
|---|---|---|---|---|
| Quality | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. |
| Adoption | 3.9K stars 0 installs | 6.0K stars 0 installs | 3.8K stars 0 installs | 44K stars 0 installs |
| Freshness | Jun 15, 2026 | Jun 9, 2026 | Jun 12, 2026 | Jun 15, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | AI Agents, Claude Code | HTML, AI Agents, Claude Code, LangChain | Python, AI Agents, Claude Code, LangChain | TypeScript, AI Agents, Claude Code |
| Warnings | No major risk signals from current metadata | No major risk signals from current metadata | No major risk signals from current metadata | No OpenAgentSkill engagement data yet |
| Best for | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | RAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signals |
| Not ideal for | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review |
| OpenAgentSkill engagement | 2 views 0 install copies | 6 views 0 install copies | 2 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add WeThinkIn/AIGC-Interview-Book | $ npx skills add adongwanai/AgentGuide | $ npx skills add LazyAGI/LazyLLM | $ npx skills add siyuan-note/siyuan |