explaining-machine-learning-models
This skill enables Claude to provide interpretability and explainability for machine learning models. It is triggered when the user requests explanations for model predictions, insights into feature importance, or help understanding model behavior. The skill leverages techniques like SHAP and LIME to generate explanations. It is useful when debugging model performance, ensuring fairness, or communicating model insights to stakeholders. Use this skill when the user mentions "explain model", "interpret model", "feature importance", "SHAP values", or "LIME explanations".
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Installation for Agentic Skill
View all platforms →skilz install jeremylongshore/claude-code-plugins-nixtla/explaining-machine-learning-models skilz install jeremylongshore/claude-code-plugins-nixtla/explaining-machine-learning-models --agent opencode skilz install jeremylongshore/claude-code-plugins-nixtla/explaining-machine-learning-models --agent codex skilz install jeremylongshore/claude-code-plugins-nixtla/explaining-machine-learning-models --agent gemini
First time? Install Skilz: pip install skilz
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/jeremylongshore/claude-code-plugins-nixtla cp -r claude-code-plugins-nixtla/archive/backups-20251108/skill-structure-cleanup-20251108-073936/plugins/ai-ml/model-explainability-tool/skills/model-explainability-tool ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- jeremylongshore (GitHub)
- Repository
- claude-code-plugins-nixtla
- Type
- Technical
- Meta-Domain
- data ai
- Primary Domain
- machine learning
- Market Score
- 17.1
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