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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

Merge To Earn is the strongest overall pick here because it has a 33/100 readiness score and fits Coding agents.

Strongest overall

Merge To Earn

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

Fastest prototype

Merge To Earn

Best first install candidate based on install readiness and adoption.

Freshest repo

Merge To Earn

Most recent maintenance signal among this shortlist.

SignalMerge To Earn

The reward system for open source development

Quality
43/100
Needs review
Decision verdict
33/100
Needs manual review

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

Adoption164 stars
0 installs
FreshnessOct 4, 2023
Use-case fit
Coding agentsGitHub automationRAG and knowledge
Workflow fit
Coding review agentContent growth agent
Platform hintsTypeScript, Developer Tools, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
Best forCoding agents 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 slice-so/merge-to-earn