model-pruning
Pass
Audited by Gen Agent Trust Hub on Sep 15, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill is a technical documentation and implementation resource for model compression. It provides legitimate code for activation-based pruning and structured sparsity patterns.
- [EXTERNAL_DOWNLOADS]: It references several well-known GitHub repositories and research papers (arXiv) including 'locuslab/wanda' and 'IST-DASLab/sparsegpt'. Per security rules, these are considered safe as they are official research sources and well-known repositories.
- [COMMAND_EXECUTION]: Provides standard commands for installing deep learning libraries (
pip install transformers torch) and cloning the aforementioned research repositories. No suspicious or obfuscated commands are present. - [DATA_EXPOSURE]: No sensitive file paths, hardcoded credentials, or exfiltration patterns were detected. The calibration data examples use public text datasets like WikiText and C4.
- [NO_OBFUSCATION]: All code and URLs are in plain text. No Base64, homoglyphs, or hidden text patterns were found.
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