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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

ICCV2019 LearningToPaint is the strongest overall pick here because it has a 76/100 readiness score and fits Coding agents.

Strongest overall

ICCV2019 LearningToPaint

Shortlist this skill and compare it with close alternatives before production adoption.

Fastest prototype

ICCV2019 LearningToPaint

Best first install candidate based on install readiness and adoption.

Freshest repo

ICCV2019 LearningToPaint

Most recent maintenance signal among this shortlist.

SignalICCV2019 LearningToPaint

ICCV2019 - Learning to Paint With Model-based Deep Reinforcement Learning

Quality
74/100
Strong
Decision verdict
76/100
Strong shortlist

Shortlist this skill and compare it with close alternatives before production adoption.

Adoption2.3K stars
0 installs
FreshnessMay 7, 2025
Use-case fit
Coding agentsRAG and knowledgeWorkflow automation
Stack fit
Content growth agentCoding review agent
Platform hintsPython, Computer Vision, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
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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
Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals
Not ideal forteams that require actively maintained dependencies · production agents without a repository review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add hzwer/ICCV2019-LearningToPaint