Skill comparison
Compare agent skills before installing.
Comparing 4 skills
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
Scikit Learn is the strongest overall pick here because it has a 100/100 readiness score and fits GitHub automation.
Strongest overall
Scikit Learn
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Scikit Learn
Best first install candidate based on install readiness and adoption.
Freshest repo
Scikit Learn
Most recent maintenance signal among this shortlist.
| Signal | Xlearn High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface. | Scikit Learn scikit-learn: machine learning in Python | Streamlit Streamlit — A faster way to build and share data apps. | Pandas Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more |
|---|---|---|---|---|
| Quality | 75/100 Strong | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 77/100 Strong shortlist Shortlist this skill and compare it with close alternatives before production adoption. | 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 | 3.1K stars Verified outcomes are shown on each skill page | 66K stars Verified outcomes are shown on each skill page | 45K stars Verified outcomes are shown on each skill page | 49K stars Verified outcomes are shown on each skill page |
| Freshness | Aug 28, 2023 | Jun 17, 2026 | Jun 14, 2026 | Jun 14, 2026 |
| Use-case fit | ||||
| Workflow fit | ||||
| Platform hints | C++, Data Analysis, Claude Code | Python, Data Analysis, Claude Code | Python, Data Analysis, Claude Code | Python, Data Analysis, 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 | Data analysis workflows · Claude Code teams · teams that value GitHub adoption signals | Data analysis 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 aksnzhy/xlearn | $ npx skills add scikit-learn/scikit-learn | $ npx skills add streamlit/streamlit | $ npx skills add pandas-dev/pandas |