Airflow
Apache Airflow workflow orchestration. Use for data pipelines.
Install
$ agentstack add skill-g1joshi-agent-skills-airflow ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Airflow
Apache Airflow is the standard for data engineering pipelines. v3.0 (2025) introduces Event-driven Triggers and a modern React UI.
When to Use
- ETL/ELT: Scheduling nightly data warehouse loads.
- ML Ops: Retraining models when new data arrives.
- Dependency Management: "Run Task B only if Task A succeeds".
Core Concepts
DAGs (Directed Acyclic Graphs)
Defined in Python.
Task SDK
New in v3.0. Allows writing tasks in any language, not just Python.
Edge Executor
Run tasks on remote edge devices.
Best Practices (2025)
Do:
- Use the TaskFlow API:
@taskdecorators are cleaner thanPythonOperator. - Use Datasets: Define data-aware scheduling (
schedule=[Dataset("s3://bucket/file")]).
Don't:
- Don't put top-level code in DAG files: It runs every scheduler heartbeat.
References
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: G1Joshi
- Source: G1Joshi/Agent-Skills
- License: MIT
- Homepage: https://skills.sh/g1joshi/agent-skills
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.