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
ML For Beginners is the strongest overall pick here because it has a 100/100 readiness score and fits GitHub automation.
Strongest overall
ML For Beginners
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
ML For Beginners
Best first install candidate based on install readiness and adoption.
Freshest repo
Cuml
Most recent maintenance signal among this shortlist.
| Signal | Tslearn The machine learning toolkit for time series analysis in Python | Darts A python library for user-friendly forecasting and anomaly detection on time series. | Cuml cuML - RAPIDS Machine Learning Library | ML For Beginners 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all |
|---|---|---|---|---|
| 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 | 3.2K stars 0 installs | 9.4K stars 0 installs | 5.2K stars 0 installs | 87K stars 0 installs |
| Freshness | Jun 12, 2026 | Jun 6, 2026 | Jun 15, 2026 | Jun 9, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Python, Machine Learning, Claude Code | Python, Machine Learning, Claude Code | Python, Machine Learning, Claude Code | Jupyter Notebook, Machine Learning, Claude Code |
| Warnings | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | Sports analytics 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 | GitHub automation 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 | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add tslearn-team/tslearn | $ npx skills add unit8co/darts | $ npx skills add rapidsai/cuml | $ npx skills add microsoft/ML-For-Beginners |