Skill audit report
Getting Things Done With Pytorch audit report.
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, dependency risk, 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
PASS86
2.5K GitHub stars
Recent maintenance
FAIL38
2y since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add curiousily/Getting-Things-Done-with-Pytorch
Repository evidence
PASS86
https://github.com/curiousily/Getting-Things-Done-with-Pytorch
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add curiousily/Getting-Things-Done-with-Pytorch
Repository
88
https://github.com/curiousily/Getting-Things-Done-with-Pytorch
License
86
Apache-2.0
Maintenance
38
2y since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Adoption
88
2.5K GitHub stars
Warnings
- Repository appears stale
- Repository looks stale
- Quality score needs review
- Recent maintenance: 2y since push
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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