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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

Surprise is the strongest overall pick here because it has a 100/100 readiness score and fits GitHub automation.

Strongest overall

Surprise

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

Fastest prototype

Surprise

Best first install candidate based on install readiness and adoption.

Freshest repo

Surprise

Most recent maintenance signal among this shortlist.

SignalSurprise

A Python scikit for building and analyzing recommender systems

Quality
100/100
Excellent
Decision verdict
100/100
Production-ready

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

Adoption6.8K stars
0 installs
FreshnessMay 30, 2026
Use-case fit
GitHub automationCoding agentsRAG and knowledge
Stack fit
Content growth agentCoding review agent
Platform hintsPython, Machine Learning, Claude Code
WarningsNo OpenAgentSkill engagement data yet
Best forGitHub automation workflows · Claude Code teams · teams that value GitHub adoption signals
OpenAgentSkill

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

GitHubX

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DocsAbout OpenAgentSkillAPIllms.txtOpenAPICLICreator KitX Growth KitSubmitBlogGuidesActivity
OpenAgentSkill Registry
PrivacyBuilt for agent-native discovery
Not ideal forteams that need a vendor-supported SLA · high-compliance environments without internal security review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add NicolasHug/Surprise