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From dagster-expert
Provides expert guidance on Dagster and dg CLI for tasks like creating projects, adding definitions, debugging issues, and querying assets, schedules, sensors, jobs, components.
npx claudepluginhub dagster-io/skills --plugin dagster-expertHow this skill is triggered — by the user, by Claude, or both
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Brief definitions only (see reference files for detailed examples):
references/asset-selection.mdreferences/assets/INDEX.mdreferences/assets/advanced-patterns.mdreferences/assets/definition-metadata.mdreferences/assets/dependencies.mdreferences/automation/choosing-automation.mdreferences/automation/declarative-automation/INDEX.mdreferences/automation/declarative-automation/advanced.mdreferences/automation/declarative-automation/core-concepts.mdreferences/automation/declarative-automation/customization.mdreferences/automation/declarative-automation/operands.mdreferences/automation/declarative-automation/operators.mdreferences/automation/schedules.mdreferences/automation/sensors/asset-sensors.mdreferences/automation/sensors/basic-sensors.mdreferences/automation/sensors/run-status-sensors.mdreferences/cli/api/INDEX.mdreferences/cli/api/agent/INDEX.mdreferences/cli/api/agent/get.mdreferences/cli/api/agent/list.mdProvides expert guidance on Dagster and the dg CLI for managing data pipelines, assets, components, and integrations.
Builds production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
Authors Apache Airflow DAGs declaratively with dag-factory YAML configs. Guides project setup, templates, defaults, dynamic/mapped tasks, datasets, callbacks, custom operators, and validation.
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Brief definitions only (see reference files for detailed examples):
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.
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.
Projects typically use uv for dependency management, and it is recommended to use it for dg commands if possible:
uv run dg list defs
uv run dg launch --assets my_asset
NEVER answer from memory or guess at CLI commands, APIs, or syntax. ALWAYS read the relevant reference file(s) from the Reference Index below before responding.
For every question, identify which reference file(s) are relevant using the index descriptions, read them, then answer based on what you read.