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.

Add more skills

Decision summary

ML Interview is the strongest overall pick here because it has a 36/100 readiness score and fits Research agents.

Strongest overall

ML Interview

Do a manual repository review before adding this to an agent workflow.

Fastest prototype

ML Interview

Best first install candidate based on install readiness and adoption.

Freshest repo

ML Interview

Most recent maintenance signal among this shortlist.

SignalML Interview

Resources I used for ML Engineer, Applied Scientist and Quant Researcher interviews.

Quality
46/100
Needs review
Decision verdict
36/100
Needs manual review

Do a manual repository review before adding this to an agent workflow.

Adoption324 stars
0 installs
FreshnessFeb 4, 2022
Use-case fit
Stack fit
Platform hintsQuant, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
Best forResearch agents workflows · Claude Code teams · builders willing to evaluate younger projects
Not ideal forteams that require actively maintained dependencies · production agents without a repository review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add mohitzsh/ML-Interview