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
Made With ML is the strongest overall pick here because it has a 100/100 readiness score and fits GitHub automation.
Strongest overall
Made With ML
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Made With ML
Best first install candidate based on install readiness and adoption.
Freshest repo
Plexe
Most recent maintenance signal among this shortlist.
| Signal | Aqueduct Aqueduct is no longer being maintained. Aqueduct allows you to run LLM and ML workloads on any cloud infrastructure. | Made With ML Learn how to develop, deploy and iterate on production-grade ML applications. | MLE Agent 🤖 MLE-Agent: Your intelligent companion for seamless AI engineering and research. 🔍 Integrate with arxiv and paper with code to provide better code/research plans 🧰 OpenAI, Anthropic, Gemini, Ollama, etc supported. :fireworks: Code RAG | Plexe ✨ Build a machine learning model from a prompt |
|---|---|---|---|---|
| Quality | 53/100 Needs review | 100/100 Excellent | 85/100 Excellent | 96/100 Excellent |
| Decision verdict | 55/100 Needs manual review Do a manual repository review before adding this to an agent workflow. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. | 87/100 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 | 519 stars 0 installs | 48K stars 0 installs | 1.6K stars 0 installs | 2.6K stars 0 installs |
| Freshness | Jun 7, 2023 | Mar 4, 2026 | Jul 27, 2025 | Mar 6, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Go, MLOps, Claude Code | Jupyter Notebook, MLOps, Claude Code | Python, MLOps, Claude Code, OpenAI Agents | Python, MLOps, Claude Code |
| Warnings | Repository looks stale · No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | GitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals | GitHub automation 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 require actively maintained dependencies · production agents without a repository 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 | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add RunLLM/aqueduct | $ npx skills add GokuMohandas/Made-With-ML | $ npx skills add MLSysOps/MLE-agent | $ npx skills add plexe-ai/plexe |