Skill UI

Provides interpretable explanations for ML predictions using SHAP, LIME, and other techniques, helping debug model behavior, highlight feature importance, and communicate fairness insights to stakeholders.

Assesses AI/ML models and datasets for ethical risks, fairness concerns, and bias, generating reports and mitigation guidance via the ai-ethics-validator plugin whenever a user requests an ethics review or bias detection.

Applies principles of behavioral economics and consumer psychology to optimize how pricing, packaging, and offers are structured and presented. This skill helps maximize the perceived value and fairness of products, guiding the use of anchors, decoy effects, and strategic framing to improve conversion rates and upsell opportunities while maintaining ethical transparency.

Conducts a comprehensive, structured ethical review for any AI or ML model, feature, or product. It assesses risks related to fairness, bias, transparency, privacy, and societal impact, providing a risk tier score, necessary mitigations, and governance documentation suitable for pre-deployment compliance.

This skill generates complete, structured, and bias-free job descriptions (JDs) for any role. It guides users through providing essential inputs, ensuring the output includes sections like role summary, responsibilities, requirements, and compensation. Crucially, it performs an inclusive language review, advising against biased requirements (like years of experience) and gendered language, thereby improving hiring fairness and attracting diverse talent.