dagster-expert

name	dagster-expert
description	Use when working with 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.
metadata	{"author":"C00ldudeNoonan"}

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.

UV Compatibility

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

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.

CRITICAL: Always Read Reference Files Before Answering

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.

Reference Index

• Asset Patterns — defining assets, dependencies, metadata, partitions, or multi-asset definitions
• Environment Variables — configuring environment variables across different environments
• Choosing an Automation Approach — deciding between schedules, sensors, and declarative automation
• Schedules — time-based automation with cron expressions
• Declarative Automation — asset-centric condition-based automation using AutomationCondition
• Asset Sensors — triggering on asset materialization events
• Basic Sensors — event-driven automation with file watching or custom polling
• Run Status Sensors — reacting to run success, failure, or other status changes
• Asset Selection Syntax — filtering assets by tag, group, kind, upstream, or downstream
• dg check — validating project configuration or definitions
• create-dagster — creating a new Dagster project from scratch

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Source: C00ldudeNoonan/economic-data-project — distributed by TomeVault.