Name: pipeline
Author: asabocinski

Prompt file imported from asabocinski/bravo-edd (.codex/prompts/pipeline.md). Copyright stays with the author.

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 pipeline-architect 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
`pipeline-architect`	Primary — DAG design, task orchestration
`spark-engineer`	Escalation — when pipeline includes Spark jobs
`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.

{ "prompt": "# Pipeline Command\n\n> Scaffold a data pipeline (Airflow, Dagster) with best-practice patterns\n\n## Usage\n\n```bash\n/pipeline <description-or-file>\n```\n\n## Examples\n\n```bash\n/pipeline \"Daily orders ETL from Postgres to Snowflake\"\n/pipeline \"Kafka → staging → dbt → marts with hourly refresh\"\n/pipeline requirements/pipeline-spec.md\n```\n\n---\n\n## What This Command Does\n\n1. Invokes the **pipeline-architect** agent\n2. Analyzes your description or requirements file\n3. Loads KB patterns from `airflow` and `dbt` domains\n4. Generates:\n - DAG structure (Airflow or Dagster)\n - Task definitions with dependencies\n - Error handling and retry configuration\n - Sensor/trigger patterns for scheduling\n\n## Agent Delegation\n\n| Agent | Role |\n|-------|------|\n| `pipeline-architect` | Primary — DAG design, task orchestration |\n| `spark-engineer` | Escalation — when pipeline includes Spark jobs |\n| `dbt-specialist` | Escalation — when pipeline includes dbt models |\n\n## KB Domains Used\n\n- `airflow` — DAG patterns, operators, sensors\n- `dbt` — model execution, incremental strategies\n- `data-quality` — quality gates between pipeline stages\n\n## Output\n\nThe agent generates pipeline code files and a summary of the DAG structure with task dependencies.", "variables": [], "notes": "DAG/pipeline scaffolding — delegates to pipeline-architect agent", "metadata": { "source": { "provider": "github-codex-prompts", "repository": "https://github.com/asabocinski/bravo-edd", "path": ".codex/prompts/pipeline.md", "ref": "ae4c539580470e782ac67d2dc4a4eabe9fc68336", "url": "https://github.com/asabocinski/bravo-edd/blob/ae4c539580470e782ac67d2dc4a4eabe9fc68336/.codex/prompts/pipeline.md", "key": "asabocinski/bravo-edd/.codex/prompts/pipeline.md" } } }

pipeline

About

Pipeline Command

Usage

Examples

What This Command Does

Agent Delegation

KB Domains Used

Output

Install pipeline and it becomes one more candidate the router can pick - when it fits.

Use it

Manifest

Reviews