{"query":"Shap","filters":{"category":null,"platform":null,"track":null,"safety":null,"include_blocked":false,"min_stars":0},"total":10,"skills":[{"rank":1,"match_score":99,"raw_match_score":1004.5,"slug":"shap-shap","name":"Shap","description":"A game theoretic approach to explain the output of any machine learning model.","tagline":"A game theoretic approach to explain the output of any machine learning model.","category":"ml-automation","tags":["machine-learning","automation","ml-media","deep-learning","explainability","gradient-boosting","interpretability","shap","shapley","jupyter notebook"],"author":{"name":"shap","verified":true,"url":"https://github.com/shap"},"attribution":{"status":"community_indexed","statusLabel":"Community indexed","shortLabel":"COMMUNITY INDEXED","sourceLabel":"GitHub star discovery","sourceDetail":"shap/shap","creatorName":"shap","creatorUrl":"https://github.com/shap","sourceUrl":"https://github.com/shap/shap","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/shap-shap#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. 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