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
Llm App is the strongest overall pick here because it has a 100/100 readiness score and fits RAG and knowledge.
Strongest overall
Llm App
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Llm App
Best first install candidate based on install readiness and adoption.
Freshest repo
Llm App
Most recent maintenance signal among this shortlist.
| Signal | Llm App Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more. | Memvid Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory. | Aichat All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI Tools & Agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more. | Happy Llm 📚 从零开始构建大模型 |
|---|---|---|---|---|
| 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 | 59K stars 0 installs | 16K stars 0 installs | 10K stars 0 installs | 31K stars 0 installs |
| Freshness | Jun 3, 2026 | May 27, 2026 | Feb 23, 2026 | May 6, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Jupyter Notebook, RAG, Claude Code | Rust, RAG, Claude Code | Rust, RAG, Claude Code, OpenAI Agents | Jupyter Notebook, RAG, Claude Code |
| Warnings | No major risk signals from current metadata | No OpenAgentSkill engagement data yet | No major risk signals from current metadata | No major risk signals from current metadata |
| Best for | RAG and knowledge workflows · Claude Code teams · teams that value GitHub adoption signals | RAG and knowledge 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 |
| 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 | 3 views 0 install copies | 0 views 0 install copies | 1 views 0 install copies | 2 views 0 install copies |
| Install | $ npx skills add pathwaycom/llm-app | $ npx skills add memvid/memvid | $ npx skills add sigoden/aichat | $ npx skills add datawhalechina/happy-llm |