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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

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

Strongest overall

Skrl

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

Fastest prototype

Skrl

Best first install candidate based on install readiness and adoption.

Freshest repo

Skrl

Most recent maintenance signal among this shortlist.

SignalSkrl

Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments

Quality
96/100
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.

Adoption1.1K stars
0 installs
FreshnessMay 11, 2026
Use-case fit
Coding agentsRAG and knowledgeWorkflow automation
Stack fit
Content growth agentCoding review agent
Platform hintsPython, Multi-Agent, Claude Code
WarningsNo OpenAgentSkill engagement data yet
Best forCoding agents 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.

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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 Toni-SM/skrl