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

Xgboost is the strongest overall pick here because it has a 100/100 readiness score and fits Sports analytics.

Strongest overall

Xgboost

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

Fastest prototype

Xgboost

Best first install candidate based on install readiness and adoption.

Freshest repo

Xgboost

Most recent maintenance signal among this shortlist.

SignalMbmlbook

Sample code for the Model-Based Machine Learning book.

Machinelearning

ML.NET is an open source and cross-platform machine learning framework for .NET.

Ml Agents

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

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
51/100
Needs review
100/100
Excellent
100/100
Excellent
100/100
Excellent
Decision verdict
41/100
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.

Adoption302 stars
0 installs
9.3K stars
0 installs
19K stars
0 installs
28K stars
0 installs
FreshnessMar 17, 2021Jun 12, 2026Jun 12, 2026Jun 16, 2026
Use-case fit
Stack fit
Platform hintsC#, Machine Learning, Claude CodeC#, Machine Learning, Claude CodeC#, Machine Learning, Claude CodeC++, Machine Learning, Claude Code
WarningsRepository looks stale · No 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 require actively maintained dependencies · production agents without a repository 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 dotnet/mbmlbook
$ npx skills add dotnet/machinelearning
$ npx skills add Unity-Technologies/ml-agents
$ npx skills add dmlc/xgboost