cosmos-dbt-core

Configure Astronomer Cosmos to integrate dbt Core projects with Airflow DAGs or TaskGroups.

2|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/miptah21/skills --skill cosmos-dbt-core-miptah21
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cosmos-dbt-core
Source: https://github.com/miptah21/skills/tree/main/.agents/skills/cosmos-dbt-core
Command: npx skills add https://github.com/miptah21/skills --skill cosmos-dbt-core-miptah21

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill removes the manual, error-prone work of wiring a dbt Core project into Airflow by generating the correct Astronomer Cosmos configuration for DAGs or TaskGroups.

Core Features & Use Cases

  • Cosmos project configuration for either dbt_project_path or manifest-based loading, including key guardrails to confirm Core (not Fusion) and manifest availability.
  • Load and execution mode selection that matches constraints such as Airflow version, containerized vs local execution, and whether you need DbtDag or DbtTaskGroup.
  • Warehouse/profile connectivity via Airflow connections and Cosmos profile mappings without hardcoding secrets, plus safe operator_args patterns for runtime dbt vars.

Use case example: You need a daily Airflow workflow that runs and tests dbt models (and optionally seeds/clones) using the same Cosmos wiring across environments while minimizing parsing overhead.

Quick Start

Use the cosmos-dbt-core skill to generate a working DbtTaskGroup in your Airflow 3 DAG by pointing it at your dbt project directory and your Airflow connection for the target warehouse.

Frequently Asked Questions about cosmos-dbt-core

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn a dbt Core project into Airflow DAGs?▼

Astronomer Cosmos integrates a dbt Core project with Airflow by generating DAGs or TaskGroups from a project path or precomputed manifest, applying the correct execution mode for your deployment environment.

What is the difference between dbt project path and manifest loading in Cosmos?▼

Loading from a dbt project path parses your project dynamically, while manifest loading uses a precomputed manifest to minimize parsing overhead and requires validating that the manifest inputs are available.

Does Cosmos support both DbtDag and DbtTaskGroup for Airflow workflows?▼

Cosmos supports configuring both DbtDag and DbtTaskGroup, allowing you to select the appropriate structure based on whether you need a standalone DAG or a nested task group within a larger Airflow workflow.

How do I map warehouse connections in Cosmos without hardcoding secrets?▼

You map warehouse connections by using Airflow connections and Cosmos ProfileConfig mappings, which securely pass credentials and environment-specific settings without hardcoding secrets in your DAG files.

Can I use this Cosmos configuration for dbt Fusion projects?▼

No, this configuration applies specifically to dbt Core projects and includes guardrails to confirm that your project is Core rather than Fusion before generating the Airflow DAGs or TaskGroups.

When should I use local execution mode versus containerized execution for dbt in Airflow?▼

Select local execution mode for simpler local testing, while containerized execution matches constraints for production deployments where dbt models run in isolated environments within Airflow.