Dagster Skills

AI assistant skills for building workflows and data pipelines using Dagster. It bundles the dagster-expert skill for authoring pipelines and the Dagster+ MCP server for access to your Dagster+ deployment.

Compatible with Claude Code, Cursor, OpenAI Codex, GitHub Copilot, OpenCode, Pi, and other Agent Skills-compatible tools.

All install paths below deliver the release-stable branch, which moves to each weekly Dagster
release. The dagster marketplace entry itself points at that branch, so the marketplace can be
added from master and still install released content.

Installation

Claude Code

Install using the
Claude plugin marketplace:

/plugin marketplace add dagster-io/skills

/plugin install dagster@dagster

/dagster-expert "What's an asset?"

Auto-update is off by default for third-party marketplaces. To pick up new releases without
reinstalling, run /plugin, open Marketplaces, select dagster, and enable auto-update.

The plugin includes the
Dagster+ MCP server, giving the skill direct
access to your deployed organization: runs, assets, deployments, code locations, alert policies,
Issues, and insights metrics. Run /mcp to authenticate.

/mcp
# authenticate dagster-plus

Fetch the run logs for the most recent run failure.

The MCP URL points at the US region by default. If your organization is in the EU region, set the following environment variable before launching Claude Code:

export DAGSTER_CLOUD_MCP_URL=https://mcp.agent.eu.dagster.cloud/mcp

Using npx skills

Install using the npx skills command-line:

npx skills add dagster-io/skills#release-stable

This installs the skill into every agent it detects (Claude Code, Codex, Cursor, Copilot, OpenCode,
Pi, and others). It copies skills only; the bundled MCP server is not configured this way.

OpenAI Codex

Codex reads the same marketplace manifest as Claude Code:

codex plugin marketplace add dagster-io/skills --ref release-stable
codex plugin add dagster@dagster

GitHub Copilot CLI

Copilot's marketplace schema has no git-subdir source, so install the plugin directly:

copilot plugin install dagster-io/skills:plugins/dagster

This tracks master; Copilot has no documented way to target a branch.

Manual Installation

git clone --branch release-stable https://github.com/dagster-io/skills.git
cp -r skills/plugins/dagster/skills/* ~/.config/opencode/skill/

git clone --branch release-stable https://github.com/dagster-io/skills.git
cp -r skills/plugins/dagster/skills/* ~/.pi/agent/skills/

Upgrading from dagster-expert

The Dagster skill now ships in a plugin named dagster rather than dagster-expert. The skill
itself is unchanged and is still invoked with /dagster-expert.

dagster-expert remains installable for now, but has become a stub that carries no Dagster guidance and only points here. To migrate:

/plugin install dagster@dagster

/plugin uninstall dagster-expert

If you install dagster without uninstalling dagster-expert, two plugins
provide a skill named dagster-expert and the deprecated stub may be used instead of the real one.

The dagster-expert plugin will be removed in a future release. After that, installations of it
report Plugin dagster-expert not found in marketplace dagster and stop loading.

Skills

dagster-expert

Expert guidance for building production-quality Dagster projects, covering CLI commands, asset patterns, automation strategies, and implementation workflows.

What you can do:

• Create and scaffold projects, assets, schedules, and sensors
• Understand asset patterns (dependencies, partitions, multi-assets, metadata)
• Implement automation (declarative automation, schedules, sensors)
• Use CLI commands (launch, list, check, scaffold, logs)
• Design project structure and configure environments
• Follow implementation workflows and best practices
• Debug issues and validate project configuration

Example prompts:

Create a new Dagster project called analytics
How do I scaffold a new asset?
Show me how to set up declarative automation
What's the proper way to partition my assets?
Help me debug why my materialization failed
How should I structure my project for multiple pipelines?
Launch all assets tagged with priority=high

Dagster+ MCP

Direct access to Dagster+ data about your deployment, including run logs, Insights, and select actions to remediate failures.

The MCP server uses your user permissions when determining the MCP server permissions. To use custom permissions, see the documentation for alternative authentication methods here

What you can do:

• Launch runs, materialize assets, re-run runs and backfills
• Fetch run logs
• Fetch asset definitions and metadata
• Fetch deployments and deployment information.
• Create and update alert policies and fetch their notifications
• Fetch Insights metrics for assets, jobs, and deployments

Example prompts:

Fetch the logs for run <run id>, investigate why it failed, and propose a solution.
What is the materialization success rate over the past month?
How often has the customer_returns_job failed in the past quarter?
What assets in my deployment are not covered by an alert policy?

Contributing

See CONTRIBUTING.md.

{
  "name": "dagster",
  "owner": {
    "name": "Dagster"
  },
  "description": "Dagster skills for CLI operations, best practices, and integrations. Dagster+ MCP server included for direct access to your deployment data.",
  "plugins": [
    {
      "name": "dagster",
      "source": {
        "source": "git-subdir",
        "url": "https://github.com/dagster-io/skills.git",
        "path": "plugins/dagster",
        "ref": "release-stable"
      },
      "description": "Comprehensive Dagster development conventions and best practices, with the Dagster+ MCP server bundled for querying your deployment."
    },
    {
      "name": "dagster-expert",
      "source": "./plugins/dagster-expert",
      "description": "Deprecated. Install dagster@dagster instead, then uninstall this plugin."
    }
  ]
}