Individual skill

shap

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

skills/general/shap/SKILL.md

Source commit df378022e8b0764e5ee07df3e3a03e2fa7c7dd65

What was checked

Matches the observed repository HEAD

Yes

Scanner rules are current

Yes

Repository scan complete

No

Skill scan complete

No

Observed behavior

Network or broad shell

Last checked

Nov 4, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

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