cellpose-cell-segmentation

Pass

Audited by Gen Agent Trust Hub on May 6, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill is a legitimate technical guide for biological image analysis. All code snippets perform standard data science tasks such as image loading, deep learning inference, visualization, and data export using established libraries.
  • [EXTERNAL_DOWNLOADS]: Includes instructions to install well-known scientific packages (cellpose, torch, scikit-image, pandas) using the standard pip package manager. It correctly references the official PyTorch index URL for CUDA-enabled versions.
  • [COMMAND_EXECUTION]: Uses basic shell commands for package installation and a simple Python one-liner to verify the installation success, which are standard practices for environment setup.
  • [DATA_EXPOSURE]: The skill interacts with local image files (TIFF/PNG) and saves results to common formats (CSV/NumPy/TIFF) for scientific analysis. No sensitive system paths, credentials, or network exfiltration patterns were detected.
Audit Metadata
Risk Level
SAFE
Analyzed
May 6, 2026, 01:47 AM
Security Audit — agent-trust-hub — cellpose-cell-segmentation