Production-ready patterns for Apache Airflow DAGs, operators, sensors, testing, and deployment.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add wshobson/agents --skill airflow-dag-patternsCompatible with
Supported agents
Covers DAG design principles (idempotent, atomic, incremental, observable) with task dependency patterns for linear, fan-out, fan-in, and complex workflows
Includes TaskFlow API decorators for cleaner code with automatic XCom passing, dynamic DAG generation from configs, and branching with conditional logic
Provides sensor patterns for S3 files, external task dependencies, and custom senso
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionairflow-dag-patternsExecute the skills CLI command in your project's root directory to begin installation:
epx add wshobson/agents --skill airflow-dag-patternsFetches airflow-dag-patterns from wshobson/agents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/airflow-dag-patterns
Restart Cursor to activate airflow-dag-patterns. Access via /airflow-dag-patternsin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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airflow-dag-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added airflow-dag-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for airflow-dag-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
airflow-dag-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in airflow-dag-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend airflow-dag-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
airflow-dag-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
airflow-dag-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: airflow-dag-patterns is focused, and the summary matches what you get after install.
airflow-dag-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
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