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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.

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Decision summary

Soccer Xg is the strongest overall pick here because it has a 40/100 readiness score and fits Sports analytics.

Strongest overall

Soccer Xg

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

Fastest prototype

Soccer Xg

Best first install candidate based on install readiness and adoption.

Freshest repo

Soccer Xg

Most recent maintenance signal among this shortlist.

SignalSoccer Xg

A Python package for training and analyzing expected goals (xG) models in soccer.

Quality
50/100
Needs review
Decision verdict
40/100
Needs manual review

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

Adoption251 stars
0 installs
FreshnessJun 4, 2024
Use-case fit
Sports analyticsCoding agentsRAG and knowledge
Stack fit
Content growth agentCoding review agent
Platform hintsJupyter Notebook, Expected Goals, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
Best forSports analytics workflows · Claude Code teams · builders willing to evaluate younger projects
OpenAgentSkill

The skill layer for AI agents: discover, compare, audit, and install reusable capabilities across Codex, Claude Code, Cursor, and agent runtimes.

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DocsAbout OpenAgentSkillAPIllms.txtOpenAPICLICreator KitX Growth KitSubmitBlogGuidesActivity
OpenAgentSkill Registry
PrivacyBuilt for agent-native discovery
Not ideal forteams that require actively maintained dependencies · production agents without a repository review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add ML-KULeuven/soccer_xg