Summary
This is your comprehensive reference for building production Airflow pipelines, covering everything from basic DAG definitions to advanced patterns like dynamic task generation, conditional branching with BranchPythonOperator, and TaskGroups for organizing complex workflows. You'll find practical examples of task dependencies (the >> and << operators, chain and cross_downstream patterns), XCom for inter-task communication, and guidance on choosing executors from LocalExecutor for dev to KubernetesExecutor for production. The skill shines when you need to orchestrate multi-step ETL workflows with dependencies, but be aware that Airflow's learning curve is real. The DAG-as-code approach is powerful once you understand concepts like catchup behavior and scheduling intervals, but debugging can be frustrating until you're familiar with the execution model.
Install to Claude Code
npx -y skills add manutej/luxor-claude-marketplace --skill apache-airflow-orchestration --agent claude-codeInstalls into .claude/skills of the current project.
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Files
SKILL.md
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Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
