Updated today
by datarobot-oss
datarobot-agent-skills
Bring DataRobot platform capabilities to your coding agents
31 GitHub stars (31)
+4 in 16 days
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- 17 skills (17 skills found in its SKILL.md files)
- 26 forks (26 forks)
- Today last update (Last updated today)
Install
Skills CLI
npx skills add datarobot-oss/datarobot-agent-skills
Asks which skills and agents to install. Just one: npx skills add datarobot-oss/datarobot-agent-skills --skill progressive-disclosure — add -g for every project.
Claude Code
git clone https://github.com/datarobot-oss/datarobot-agent-skillscp -r "datarobot-agent-skills/.skills/progressive-disclosure" ~/.claude/skills/
Copies the progressive-disclosure skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.
Plugin
/plugin marketplace add datarobot-oss/datarobot-agent-skills
Run inside Claude Code if the repository ships a plugin marketplace, then pick plugins from /plugin.
Skills can run code on your machine — read the SKILL.md first.
What it does
In the author's own words, from each skill's SKILL.md.
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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.
.skills/progressive-disclosure/SKILL.md on GitHub (opens in a new tab) -
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, swarm simulation, 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…
skills/datarobot-agent-assist/SKILL.md on GitHub (opens in a new tab) -
datarobot-agent-llm-selection
Use when the user wants to configure LLM integration for a DataRobot agent application. This skill helps to change LLM model, switch between the LLM integrations the project supports (LLM Gateway, a DataRobot-deployed LLM, an external provider, an LLM Blueprint, and any others its config declares), or set up provider credentials. The skill reads the project's .datarobot/cli/llm.yml for the real o…
skills/datarobot-agent-llm-selection/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-app-framework-cicd/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-data-preparation/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-discover/SKILL.md on GitHub (opens in a new tab) -
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, wants to send agent traces, logs, or metrics to DataRobot, or wants to record and replay agent trajectorie…
skills/datarobot-external-agent-monitoring/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-feature-engineering/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-model-deployment/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-model-explainability/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-model-monitoring/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-model-training/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-predictions/SKILL.md on GitHub (opens in a new tab) -
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.
skills/datarobot-setup/SKILL.md on GitHub (opens in a new tab) -
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: deploy a container as a managed service; list/start/stop workloads; change replica counts or autoscaling; pick CPU/GPU compute bundles; inject DataRobot credentials as env vars; diagnose stuck/errored/crash-looping workloads (CrashLoopBackOff, ImagePullBackOf…
skills/datarobot-workload-api/SKILL.md on GitHub (opens in a new tab) -
datarobot-agent-assist-build
Use when the user wants to design, build, code, or deploy an AI agent on DataRobot; mentions agent_spec.md, dress rehearsal, the DataRobot agent template, LangGraph, CrewAI, LlamaIndex, NAT, Base agents, MCP servers, backend APIs, custom frontends, or the DataRobot CLI.
skills/datarobot-agent-assist/agent-assist-build/SKILL.md on GitHub (opens in a new tab) -
datarobot-agent-assist-simulate
Use when the user wants to adversarially test, evaluate, or harden an implemented AI agent before deployment; mentions swarm simulation, attack testing, persistence testing, evaluation criteria, or eval_report.md.
skills/datarobot-agent-assist/agent-assist-simulate/SKILL.md on GitHub (opens in a new tab)
No skill matches that filter.
Review before you install
A skill is a set of instructions and scripts your agent will follow, and it can run code on your machine. Read the SKILL.md and any scripts first — this listing is not a security review.