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 1 skill
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
Machine Learning For Physicists is the strongest overall pick here because it has a 70/100 readiness score and fits Coding agents.
Strongest overall
Machine Learning For Physicists
Prototype with this skill first; keep a fallback candidate ready.
Fastest prototype
Machine Learning For Physicists
Best first install candidate based on install readiness and adoption.
Freshest repo
Machine Learning For Physicists
Most recent maintenance signal among this shortlist.
| Signal | Machine Learning For Physicists Code for "Machine Learning for Physicists" lecture series by Florian Marquardt |
|---|---|
| Quality | 71/100 Strong |
| Decision verdict | 70/100 Prototype first Prototype with this skill first; keep a fallback candidate ready. |
| Adoption | 335 stars 0 installs |
| Freshness | May 14, 2026 |
| Use-case fit | |
| Workflow fit | |
| Platform hints | Jupyter Notebook, Machine Learning, Claude Code |
| Warnings | No OpenAgentSkill engagement data yet |
| Best for | Coding agents workflows · Claude Code teams · builders willing to evaluate younger projects |
| Not ideal for | teams that need a vendor-supported SLA · high-compliance environments without internal security review |
| OpenAgentSkill engagement | 0 views 0 install copies |
| Install | $ npx skills add FlorianMarquardt/machine-learning-for-physicists |