datarobot-model-explainability
Tools and guidance for model explainability, prediction explanations, feature impact analysis, SHAP values, SHAP distributions, anomaly assessment, and model diagnostics. Use when analyzing model explanations, feature impact, SHAP values, SHAP distributions, anomaly assessment, or diagnosing model behavior.
Install
With your agent
Install OMGSkills skill "datarobot-oss/datarobot-agent-skills:skills/datarobot-model-explainability" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/datarobot-oss/datarobot-agent-skills /tmp/datarobot-agent-skills && ln -s /tmp/datarobot-agent-skills/skills/datarobot-model-explainability ~/.claude/skills/datarobot-model-explainabilityFrom README
DataRobot Model Explainability Skill This skill covers SHAP insights, XEMP prediction explanations, anomaly explanations, and model diagnostics. SDK version: Use datarobot>=3.6.0 for the full API set in this skill (ShapDistributions was added in 3.6; ShapMatrix, ShapImpact, and ShapPreview are available in datarobot>=3.4.0). Use from datarobot.insights import ShapMatrix, ... with entityid=modelid — not legacy datarobot.models.ShapMatrix (projectid / datasetid). ShapMatrix, ShapImpact, ShapPreview, and ShapDistributions are the canonical SHAP API. The older dr.PredictionExplanations (XEMP-based) remains available but is the secondary path.
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