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 For Beginners is the strongest overall pick here because it has a 100/100 readiness score and fits Data analysis.
Strongest overall
Data Science For Beginners
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Data Science For Beginners
Best first install candidate based on install readiness and adoption.
Freshest repo
Hamilton
Most recent maintenance signal among this shortlist.
| Signal | Hamilton Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does. | Data Science For Beginners 10 Weeks, 20 Lessons, Data Science for All! | DataFrame C++ DataFrame for statistical, financial, and ML analysis in modern C++ | ArcticDB ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem. |
|---|---|---|---|---|
| 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 | 2.5K stars 0 installs | 36K stars 0 installs | 3.0K stars 0 installs | 2.4K stars 0 installs |
| Freshness | Jun 14, 2026 | Jun 10, 2026 | Jun 13, 2026 | Jun 14, 2026 |
| Use-case fit | ||||
| Stack fit | ||||
| Platform hints | Jupyter Notebook, Data Analysis, Claude Code | Jupyter Notebook, Data Analysis, Claude Code | C++, Data Analysis, Claude Code | C++, Data Analysis, Claude Code |
| Warnings | No major risk signals from current metadata | No major risk signals from current metadata | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | Data analysis workflows · Claude Code teams · teams that value GitHub adoption signals | Data analysis 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 |
| 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 | 2 views 0 install copies | 4 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add apache/hamilton | $ npx skills add microsoft/Data-Science-For-Beginners | $ npx skills add hosseinmoein/DataFrame | $ npx skills add man-group/ArcticDB |