The Agent Skills Directory

[SAFE]: The skill provides legitimate guidance and Python code for explainable AI in the context of omics data. The code examples are purely functional for data analysis and do not include any patterns for exfiltration, persistence, or privilege escalation.
[INDIRECT_PROMPT_INJECTION]: The skill instructions involve processing user-provided omics data and machine learning models. It addresses the inherent attack surface by providing extensive documentation on the boundaries of model attribution, explicitly warning that these methods explain model internals rather than providing biological proof, which acts as a conceptual safeguard for the agent.
[EXTERNAL_DOWNLOADS]: The skill references the installation of standard, well-known scientific libraries including shap, lime, scikit-learn, xgboost, and pandas. These dependencies are reputable within the research community and are used according to best practices.

bio-machine-learning-prediction-explanation