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.
Decision summary
FEAT is the strongest overall pick here because it has a 43/100 readiness score and fits Coding agents.
Strongest overall
FEAT
Do a manual repository review before adding this to an agent workflow.
Fastest prototype
FEAT
Best first install candidate based on install readiness and adoption.
Freshest repo
FEAT
Most recent maintenance signal among this shortlist.
| Signal | FEAT The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions" |
|---|---|
| Quality | 53/100 Needs review |
| Decision verdict | 43/100 Needs manual review Do a manual repository review before adding this to an agent workflow. |
| Adoption | 434 stars 0 installs |
| Freshness | Jul 31, 2020 |
| Use-case fit | |
| Workflow fit | |
| Platform hints | Python, Computer Vision, Claude Code |
| Warnings | Repository looks stale · No OpenAgentSkill engagement data yet |
| Best for | Coding agents workflows · Claude Code teams · builders willing to evaluate younger projects |
| Not ideal for | teams that require actively maintained dependencies · production agents without a repository review |
| OpenAgentSkill engagement | 0 views 0 install copies |
| Install | $ npx skills add Sha-Lab/FEAT |