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.

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Decision summary

CLIP is the strongest overall pick here because it has a 100/100 readiness score and fits Coding agents.

Strongest overall

CLIP

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Fastest prototype

CLIP

Best first install candidate based on install readiness and adoption.

Freshest repo

Scholar

Most recent maintenance signal among this shortlist.

SignalScholar

Traditional machine learning on top of Nx

Pytorch Lightning

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Quality
78/100
Strong
100/100
Excellent
100/100
Excellent
100/100
Excellent
Decision verdict
77/100
Strong shortlist

Shortlist this skill and compare it with close alternatives before production adoption.

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.

Adoption496 stars
Verified outcomes are shown on each skill page
31K stars
Verified outcomes are shown on each skill page
34K stars
Verified outcomes are shown on each skill page
28K stars
Verified outcomes are shown on each skill page
FreshnessJul 15, 2026Jun 10, 2026Mar 25, 2026Jun 16, 2026
Use-case fit
Workflow fit
Platform hintsElixir, Machine Learning, Claude CodePython, Machine Learning, Claude CodeJupyter Notebook, Machine Learning, Claude CodeC++, Machine Learning, Claude Code
WarningsNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yetNo OpenAgentSkill engagement data yet
Best forCoding agents workflows · Claude Code teams · builders willing to evaluate younger projectsCoding agents workflows · Claude Code teams · teams that value GitHub adoption signalsCoding agents workflows · Claude Code teams · teams that value GitHub adoption signalsSports analytics workflows · Claude Code teams · teams that value GitHub adoption signals
Not ideal forteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security reviewteams that need a vendor-supported SLA · high-compliance environments without internal security review
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Install
$ npx skills add elixir-nx/scholar
$ npx skills add Lightning-AI/pytorch-lightning
$ npx skills add openai/CLIP
$ npx skills add dmlc/xgboost