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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

LearningByCheating is the strongest overall pick here because it has a 42/100 readiness score and fits Sports analytics.

Strongest overall

LearningByCheating

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

Fastest prototype

LearningByCheating

Best first install candidate based on install readiness and adoption.

Freshest repo

LearningByCheating

Most recent maintenance signal among this shortlist.

SignalLearningByCheating

(CoRL 2019) Driving in CARLA using waypoint prediction and two-stage imitation learning

Quality
52/100
Needs review
Decision verdict
42/100
Needs manual review

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

Adoption340 stars
0 installs
FreshnessApr 18, 2022
Use-case fit
Sports analyticsCoding agentsRAG and knowledge
Stack fit
Content growth agentCoding review agent
Platform hintsPython, Robotics, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
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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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PrivacyBuilt for agent-native discovery
Sports analytics 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 dotchen/LearningByCheating