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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

Class Balanced Loss Pytorch is the strongest overall pick here because it has a 57/100 readiness score and fits Coding agents.

Strongest overall

Class Balanced Loss Pytorch

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

Fastest prototype

Class Balanced Loss Pytorch

Best first install candidate based on install readiness and adoption.

Freshest repo

Class Balanced Loss Pytorch

Most recent maintenance signal among this shortlist.

SignalClass Balanced Loss Pytorch

Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

Quality
55/100
Promising
Decision verdict
57/100
Needs manual review

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

Adoption803 stars
0 installs
FreshnessFeb 18, 2024
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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PrivacyBuilt for agent-native discovery
Best forCoding 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 vandit15/Class-balanced-loss-pytorch