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airflow-dag-patterns from ghosteken/agent-harness is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
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.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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
1. Identify data sources, schedules, and dependencies.
2. Design idempotent tasks with clear ownership and retries.
3. Implement DAGs with observability and alerting hooks.
4. Validate in staging and document operational runbooks.
Refer to `resources/implementation-playbook.md` for detailed patterns, checklists, and templates.
## Safety
- Avoid changing production DAG schedules without approval.
- Test backfills and retries carefully to prevent data duplication.
## Resources
- `resources/implementation-playbook.md` for detailed patterns, checklists, and templates.
## Limitations
…
The line at the top of this page pins the label git:20260721.efafd9c, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
GET https://markdownregistry.com/api/v1/artifacts/art_nepa7k2fjfd5utba
GET https://markdownregistry.com/api/v1/resolve?ref=ghosteken/agent-harness/airflow-dag-patterns
GET https://markdownregistry.com/api/v1/blob/94a41e7557ed0038de304d942691a6f432f6a29b82dc096e7c1f265b74fc332c
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