dagster-expert
Expert guidance for Dagster projects, asset definitions, and dg CLI workflows.
- Provides deep knowledge of Dagster concepts (assets, components, schedules, sensors, jobs) and helps with project structure, debugging, and codebase navigation
- Covers the
dgCLI for common tasks: creating projects, scaffolding definitions, listing assets, launching runs, and exploring project structure - Includes guidance on automation approaches (schedules, sensors, declarative automation) and integration patterns with 40+ external tools
- Always references official documentation before answering; use
--jsonflags for machine-readable CLI output anduvfor dependency management
Core Dagster Concepts
Brief definitions only (see reference files for detailed examples):
- Asset: Persistent object (table, file, model) produced by your pipeline
- Component: Reusable building block that generates definitions (assets, schedules, sensors, jobs, etc.) relevant to a particular domain.
Integration Workflow
When integrating with ANY external tool or service, read the Integration libraries index. This contains information about which integration libraries exist, and references on how to create new custom integrations for tools that do not have a published library.
dg CLI
The dg CLI is the recommended way to programmatically interact with Dagster (adding definitions, launching runs, exploring project structure, etc.). It is installed as part of the dagster-dg-cli package. If a relevant CLI command for a given task exists, always attempt to use it.
ONLY explore the existing project structure if it is strictly necessary to accomplish the user's goal. In many cases, existing CLI tools will have sufficient understanding of the project structure, meaning listing and reading existing files is wasteful and unnecessary.
Almost all dg commands that return information have a --json flag that can be used to get the information in a machine-readable format. This should be preferred over the default table output unless you are directly showing the information to the user.
More from dagster-io/skills
dignified-python
Opinionated production Python standards with automatic version detection (3.10-3.13). Use when
1.2Kdagster-integrations
Skill that helps users discover and understand Dagster integration libraries. Used when users have requests related to
124dagster-best-practices
Expert guidance for Dagster data orchestration including assets, resources, automation, testing,
15dg
Skill that enables interaction with Dagster projects (creating new projects, generating new definitions within existing projects, listing definitions, launching compute, viewing logs, and troubleshooting). Used whenever users have requests related to creating, understanding, or manipulating Dagster projects.
12