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
Data Science Interviews is the strongest overall pick here because it has a 100/100 readiness score and fits GitHub automation.
Strongest overall
Data Science Interviews
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Data Science Interviews
Best first install candidate based on install readiness and adoption.
Freshest repo
Catboost
Most recent maintenance signal among this shortlist.
| Signal | Pixie Instant Kubernetes-Native Application Observability | Catboost A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU. | Serving A flexible, high-performance serving system for machine learning models | Data Science Interviews Data science interview questions and answers |
|---|---|---|---|---|
| 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 | 6.5K stars 0 installs | 9.0K stars 0 installs | 6.4K stars 0 installs | 10K stars 0 installs |
| Freshness | Jun 10, 2026 | Jun 12, 2026 | Jun 13, 2026 | Jun 1, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | C++, Machine Learning, Claude Code | C++, Machine Learning, Claude Code | C++, Machine Learning, Claude Code | HTML, 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 | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals | Workflow 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 pixie-io/pixie | $ npx skills add catboost/catboost | $ npx skills add tensorflow/serving | $ npx skills add alexeygrigorev/data-science-interviews |