frank-luongt/plugins/faos-data-engineer/skills/airflow-dag-patterns
plugins/faos-data-engineer/skills/airflow-dag-patterns/SKILL.md
<!-- AUTO-GENERATED by export-plugins.py — DO NOT EDIT --> --- name: airflow-dag-patterns description: Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs. tags: [ai, data-engineering] --- # Apache Airflow DAG Patterns Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies. ## Use this skill
$ install --global
skillsauthnpx skillsauth add frank-luongt/faos-skills-marketplace plugins/faos-data-engineer/skills/airflow-dag-patternsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
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TrivyContainer and dependency vulnerability scanner
95%
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SemgrepStatic code analysis for vulnerabilities
95%
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mcp-scan (Snyk)Model Context Protocol security validation
95%
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Snyk (dep)Open source security scanning
50%
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Socket.devSupply chain security analysis
50%
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VirusTotalMulti-engine malware detection
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OWASP Dep-Check
50%
Last scanned: Apr 20, 2026, 2:58 PM7.1s1 file scanned
SKILL.md
<!-- AUTO-GENERATED by export-plugins.py — DO NOT EDIT -->
name: airflow-dag-patterns description: Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs. tags: [ai, data-engineering]
Apache Airflow DAG Patterns
Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies.
Use this skill when
- Creating data pipeline orchestration with Airflow
- Designing DAG structures and dependencies
- Implementing custom operators and sensors
- Testing Airflow DAGs locally
- Setting up Airflow in production
- Debugging failed DAG runs
Do not use this skill when
- You only need a simple cron job or shell script
- Airflow is not part of the tooling stack
- The task is unrelated to workflow orchestration
Instructions
- Identify data sources, schedules, and dependencies.
- Design idempotent tasks with clear ownership and retries.
- Implement DAGs with observability and alerting hooks.
- Validate in staging and document operational runbooks.
Safety
- Avoid changing production DAG schedules without approval.
- Test backfills and retries carefully to prevent data duplication.
Resources
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