datarobot-oss/datarobot-agent-skills
14 skills
$npx skills add datarobot-oss/datarobot-agent-skillsSkillInstalls
datarobot-agent-assistUse when the user wants to design, build, code, simulate, or deploy an AI agent (not a predictive model) to DataRobot; mentions agent_spec.md, dr-assist, datarobot-agent-assist, dress rehearsal, or thdatarobot-app-framework-cicdGuidance for setting up CI/CD pipelines for DataRobot application templates using GitLab, GitHub Actions, and Pulumi for infrastructure as code. Use when setting up CI/CD pipelines, configuring deploydatarobot-data-preparationTools and guidance for data upload, dataset management, data validation, and preparing data for DataRobot projects. Use when uploading datasets, managing data, or validating data for DataRobot.datarobot-discoverUse when the user wants to find DataRobot capabilities — skills, MCP servers, agents, or platform resources — for a task. Fetches the live DataRobot catalog directly so results are always current, regdatarobot-external-agent-monitoringInstrument any external or existing AI agent with OpenTelemetry to send traces, logs, and metrics to DataRobot for monitoring, observability, and governance. Use when the user says "add tracing/observdatarobot-feature-engineeringGuidance for feature engineering, feature discovery, feature importance analysis, and understanding DataRobot's automated feature engineering capabilities. Use when working with feature engineering, fdatarobot-model-deploymentTools and guidance for deploying DataRobot models, managing deployments, configuring prediction environments, and deployment operations. Use when deploying models, creating or updating deployments, ordatarobot-model-explainabilityTools and guidance for model explainability, prediction explanations, feature impact analysis, SHAP values, SHAP distributions, anomaly assessment, and model diagnostics. Use when analyzing model expldatarobot-model-monitoringTools and guidance for monitoring model performance, tracking data drift, managing model health, and detecting prediction anomalies. Use when monitoring deployed models, tracking drift, or investigatidatarobot-model-trainingComprehensive guidance for training models in DataRobot, including project creation, AutoML configuration, feature engineering, and model selection. Use when training models, creating AutoML projects,datarobot-predictionsTools and guidance for making predictions with DataRobot deployments, including real-time predictions, batch scoring, prediction dataset generation, and prediction explanations (SHAP/XEMP). Use when mdatarobot-setupSets up DataRobot for local development including Python SDK, dr-cli, Agent Assist, and all required dependencies. Use when the user has not yet worked with DataRobot on this machine, OR when any Datadatarobot-workload-apiUse when the user wants to create, configure, scale, debug, observe, or roll out container workloads on DataRobot's Workload API. Triggers include: deploying a container as a managed service, listing/progressive-disclosureRefactor large DataRobot skill files by moving detailed content into directly linked reference files while preserving meaning. Use when a skill triggers context-window warnings, needs progressive disc