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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

CrazyAra is the strongest overall pick here because it has a 71/100 readiness score and fits GitHub automation.

Strongest overall

CrazyAra

Prototype with this skill first; keep a fallback candidate ready.

Fastest prototype

CrazyAra

Best first install candidate based on install readiness and adoption.

Freshest repo

CrazyAra

Most recent maintenance signal among this shortlist.

SignalCrazyAra

A Deep Learning UCI-Chess Variant Engine written in C++ & Python :parrot:

Quality
72/100
Strong
Decision verdict
71/100
Prototype first

Prototype with this skill first; keep a fallback candidate ready.

Adoption289 stars
0 installs
FreshnessMar 2, 2026
Use-case fit
GitHub automationCoding agentsRAG and knowledge
Workflow fit
Content growth agentCoding review agent
Platform hintsJupyter Notebook, Machine Learning, Claude Code
WarningsNo OpenAgentSkill engagement data yet
Best forGitHub automation 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 need a vendor-supported SLA · high-compliance environments without internal security review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add QueensGambit/CrazyAra