airflow-dag-patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment
Install / Use
npx skills add sickn33/agentic-awesome-skills --skill airflow-dag-patternsInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Our assessment of airflow-dag-patterns
airflow-dag-patterns scores 77/100 on our quality scale, 948th of 1,264 Automation skills we index.
Its SKILL.md is 1.8 KB long, split into 7 sections and no code examples: moderately detailed.
With 46,875 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated yesterday, so airflow-dag-patterns is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
airflow-dag-patterns compared with similar skills
All 4 of these similar skills score higher than airflow-dag-patterns; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| airflow-dag-patterns (this skill)by sickn33 | 77 | 46.9k | 1d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.5k | 10d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.3k | 1d ago | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 83.7k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
Frequently asked questions
- How do I install airflow-dag-patterns?
- Run
npx skills add sickn33/agentic-awesome-skills --skill airflow-dag-patterns. The install tabs above show the steps for each supported agent. - Which AI agents does airflow-dag-patterns work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is airflow-dag-patterns safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is airflow-dag-patterns still maintained?
- The repository was last updated yesterday, so airflow-dag-patterns is actively maintained.
Skill content
View source on GitHubname: 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." risk: safe source: community date_added: "2026-02-27"
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.
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.mdfor detailed patterns, checklists, and templates.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Related Skills
Agent-Reach
85.5kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
ruflo
73.3k🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Scrapling
83.7k🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl! Don't be shy, join here: https://discord.gg/EMgGbDceNQ and follow here for daily tips and tricks: https://x.com/Scrapling_dev
algorithmic-art
177.9kCreating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.