Production-ready patterns for Apache Airflow DAGs, operators, sensors, testing, and deployment.
Run in your terminal
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:
Package manager
npx skills add https://github.com/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:
Restart Cursor to activate airflow-dag-patterns. Access via /airflow-dag-patternsin your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Save 3-5 hours per week on routine tasks
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Package manager
npx skills add https://github.com/wshobson/agents --skill airflow-dag-patternsWorks with
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Time Estimate
15-45 minutes depending on use case complexity
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✓ 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.
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Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
wshobson/agents
wshobson/agents
wshobson/agents
giuseppe-trisciuoglio/developer-kit
giuseppe-trisciuoglio/developer-kit
davila7/claude-code-templates
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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