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
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
Catboost
Most recent maintenance signal among this shortlist.
| Signal | PZAD Курс "Прикладные задачи анализа данных" (ВМК, МГУ имени М.В. Ломоносова) | ML For Beginners 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all | Pyod A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents. | 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. |
|---|---|---|---|---|
| Quality | 47/100 Needs review | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 37/100 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. | 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 | 339 stars 0 installs | 87K stars 0 installs | 9.9K stars 0 installs | 9.0K stars 0 installs |
| Freshness | Aug 29, 2022 | Jun 9, 2026 | Jun 5, 2026 | Jun 12, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Machine Learning, Claude Code | Jupyter Notebook, Machine Learning, Claude Code | Python, Machine Learning, Claude Code | C++, Machine Learning, 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 · builders willing to evaluate younger projects | GitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals | GitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals | Workflow automation 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 Dyakonov/PZAD | $ npx skills add microsoft/ML-For-Beginners | $ npx skills add yzhao062/pyod | $ npx skills add catboost/catboost |