Skill audit report
Pytorch CycleGAN And Pix2pix audit report.
Image-to-Image Translation in PyTorch
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, install safety, permission surface, and installability.
The Trust Score is OpenAgentSkill's adoption layer. It is designed to help an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS100
25K GitHub stars
Stars/forks activity
PASS100
25K stars, 6.6K forks; issue activity unavailable in current metadata
Recent maintenance
INFO62
10mo since push
License clarity
WARN42
Unknown
README/SKILL.md completeness
INFO74
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add junyanz/pytorch-CycleGAN-and-pix2pix
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO72
filesystem or document access, network or browser access
Repository evidence
PASS86
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add junyanz/pytorch-CycleGAN-and-pix2pix
Repository
88
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
License
45
Unknown
Maintenance
62
10mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
84
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
72
filesystem or document access, network or browser access
Stars/forks activity
100
25K stars, 6.6K forks; issue activity unavailable in current metadata
Adoption
88
25K GitHub stars
Warnings
- License is unclear
- License clarity: Unknown
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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