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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

Opencv Facial Landmark Detection is the strongest overall pick here because it has a 34/100 readiness score and fits GitHub automation.

Strongest overall

Opencv Facial Landmark Detection

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

Fastest prototype

Opencv Facial Landmark Detection

Best first install candidate based on install readiness and adoption.

Freshest repo

Opencv Facial Landmark Detection

Most recent maintenance signal among this shortlist.

SignalOpencv Facial Landmark Detection

使用OpenCV实现人脸关键点检测

Quality
44/100
Needs review
Decision verdict
34/100
Needs manual review

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

Adoption197 stars
0 installs
FreshnessApr 8, 2018
Use-case fit
GitHub automationCoding agentsRAG and knowledge
Stack fit
Content growth agentCoding review agent
Platform hintsC++, Computer Vision, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
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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OpenAgentSkill Registry
PrivacyBuilt for agent-native discovery
Best forGitHub automation workflows · Claude Code teams · builders willing to evaluate younger projects
Not ideal forteams that require actively maintained dependencies · production agents without a repository review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add amusi/opencv-facial-landmark-detection