Skill
airflow-hitl
Builds human-in-the-loop (HITL) Airflow workflows - approval gates, form input, and human-driven branching. Use when a DAG needs a human in the loop - an…
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Skill
/airflow-adapter
Airflow adapter pattern for v2/v3 API compatibility. Use when working with adapters, version detection, or adding new API methods that need to work across Airflow 2.x and 3.x.
Install
$ npx -y skills add astronomer/agents --skill airflow-adapter --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/airflow-adapter
Context preview
The summary Claude sees to decide when to auto-load this skill.
Airflow adapter pattern for v2/v3 API compatibility. Use when working with adapters, version detection, or adding new API methods that need to work across Airflow 2.x and 3.x.
SKILL.md
airflow-adapter.SKILL.mdname: airflow-adapter description: Airflow adapter pattern for v2/v3 API compatibility. Use when working with adapters, version detection, or adding new API methods that need to work across Airflow 2.x and 3.x.
Airflow Adapter Pattern
Enables compatibility with both Airflow 2.x (`/api/v1`) and 3.x (`/api/v2`).
Architecture
MCP Tool → _get_adapter() → AirflowV2Adapter or AirflowV3Adapter → Airflow API
Version is auto-detected at startup.
Key Files
- `adapters/base.py` - Abstract interface
- `adapters/airflow_v2.py` - Airflow 2.x (`/api/v1`)
- `adapters/airflow_v3.py` - Airflow 3.x (`/api/v2`)
Related Files
- @api-differences.md - V2 vs V3 field/endpoint differences
- @patterns.md - Implementation patterns
Quick Reference
adapter = _get_adapter()
dags = adapter.list_dags(limit=100)
run = adapter.trigger_dag_run("my_dag", conf={"key": "value"}) Ships withastronomer-data
AI agent tooling for data engineering workflows. Includes an MCP server for Airflow, a CLI tool (af) for interacting with Airflow from your terminal, and skills that extend AI coding agents with specialized capabilities for working with Airflow and data
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