datarobot-agent-skills
ListedBring DataRobot platform capabilities to your coding agents
Bundles
Everything this plugin ships — skills, agents, commands, hooks, and MCP servers it bundles.
Skills (14)
progressive-disclosure
Refactor 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 disclosure, or should be chunked without changing guidance.
datarobot-agent-assist
Use 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 the DataRobot agent template; wants to scaffold a LangGraph, CrewAI, LlamaIndex, NAT, or Base agent targeting DataRobot; wants to add an MCP server, backend API, or React frontend to a DataRobot agent application; or uses the DataRobot CLI (dr) to build or deploy an agentic custom application. Covers the full workflow: agent design, agent_spec.md authoring, dress-rehearsal simulation via the DataRobot LLM Gateway, template-based coding, and deployment.
datarobot-app-framework-cicd
Guidance 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 deployments, or managing infrastructure for DataRobot application templates.
datarobot-data-preparation
Tools 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-discover
Use 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, regardless of third-party search index lag. Also checks the user's own DataRobot instance if DATAROBOT_ENDPOINT is set.
datarobot-external-agent-monitoring
Instrument 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/observability/monitoring to my agent", wants to instrument an existing agent project in their IDE, or wants to send agent traces, logs, or metrics to DataRobot.
datarobot-feature-engineering
Guidance for feature engineering, feature discovery, feature importance analysis, and understanding DataRobot's automated feature engineering capabilities. Use when working with feature engineering, feature discovery, or analyzing feature importance in DataRobot.
datarobot-model-deployment
Tools and guidance for deploying DataRobot models, managing deployments, configuring prediction environments, and deployment operations. Use when deploying models, creating or updating deployments, or configuring prediction environments.
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.
datarobot-model-monitoring
Tools and guidance for monitoring model performance, tracking data drift, managing model health, and detecting prediction anomalies. Use when monitoring deployed models, tracking drift, or investigating prediction anomalies.
datarobot-model-training
Comprehensive guidance for training models in DataRobot, including project creation, AutoML configuration, feature engineering, and model selection. Use when training models, creating AutoML projects, or selecting models in DataRobot.
datarobot-predictions
Tools and guidance for making predictions with DataRobot deployments, including real-time predictions, batch scoring, prediction dataset generation, and prediction explanations (SHAP/XEMP). Use when making predictions, running batch scoring, generating prediction datasets, or explaining individual predictions from a deployment.
Show all 14 bundled skills Showing all 14 bundled skills
datarobot-setup
Sets 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 DataRobot task fails due to missing or invalid credentials. Covers first-time setup, re-authentication, and credential recovery.
datarobot-workload-api
Use 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/starting/stopping workloads, changing replica counts or autoscaling, picking CPU/GPU compute bundles, injecting DataRobot credentials as env vars, diagnosing workloads that are stuck / errored / crash-looping (CrashLoopBackOff, ImagePullBackOff, OOMKilled, probe failures, exec format error), pulling application logs / OpenTelemetry traces / metrics / request stats, creating or iterating container artifacts, building images server-side, locking artifacts for production, or doing a zero-downtime rolling artifact replacement.
Quality Score: 57/100
Details
- Author
- datarobot-oss
- Repository
- datarobot-oss/datarobot-agent-skills
- Created
- 7 months ago
- Last Updated
- 3 days ago
- Language
- Python
- License
- Apache-2.0