| name | pipeline |
| description | DAG/pipeline scaffolding — delegates to architect-pipeline agent. Use when
scaffolding Airflow or Dagster pipelines with best-practice patterns.
|
Pipeline Command
Scaffold a data pipeline (Airflow, Dagster) with best-practice patterns
Usage
/pipeline <description-or-file>
Examples
/pipeline "Daily orders ETL from Postgres to Snowflake"
/pipeline "Kafka → staging → dbt → marts with hourly refresh"
/pipeline requirements/pipeline-spec.md
What This Command Does
- Invokes the architect-pipeline agent
- Analyzes your description or requirements file
- Loads KB patterns from
airflow and dbt domains
- Generates:
- DAG structure (Airflow or Dagster)
- Task definitions with dependencies
- Error handling and retry configuration
- Sensor/trigger patterns for scheduling
Agent Delegation
| Agent | Role |
|---|
architect-pipeline | Primary — DAG design, task orchestration |
de-spark-engineer | Escalation — when pipeline includes Spark jobs |
de-dbt-specialist | Escalation — when pipeline includes dbt models |
KB Domains Used
airflow — DAG patterns, operators, sensors
dbt — model execution, incremental strategies
data-quality — quality gates between pipeline stages
Output
The agent generates pipeline code files and a summary of the DAG structure with task dependencies.