# Data Pipeline

> ETL/ELT pipeline design. Trigger when the user wants to create data flows, transformations, or orchestration.

- **Type:** Skill
- **Install:** `agentstack add skill-christopherlouet-claude-base-data-pipeline`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [christopherlouet](https://agentstack.voostack.com/s/christopherlouet)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [christopherlouet](https://github.com/christopherlouet)
- **Source:** https://github.com/christopherlouet/claude-base/tree/main/.claude/skills/data-pipeline
- **Website:** https://christopherlouet.github.io/claude-base/

## Install

```sh
agentstack add skill-christopherlouet-claude-base-data-pipeline
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Data Pipeline

## ETL vs ELT

| Pattern | When to use |
|---------|----------------|
| ETL | Complex transformation, sensitive data |
| ELT | Big data, cloud DW (BigQuery, Snowflake) |

## Airflow DAG

```python
from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime, timedelta

default_args = {
    'owner': 'data-team',
    'retries': 3,
    'retry_delay': timedelta(minutes=5),
}

with DAG(
    'daily_etl',
    default_args=default_args,
    schedule_interval='0 2 * * *',
    start_date=datetime(2024, 1, 1),
    catchup=False,
) as dag:

    extract = PythonOperator(
        task_id='extract',
        python_callable=extract_from_source,
    )

    transform = PythonOperator(
        task_id='transform',
        python_callable=transform_data,
    )

    load = PythonOperator(
        task_id='load',
        python_callable=load_to_warehouse,
    )

    extract >> transform >> load
```

## dbt Transformation

```sql
-- models/staging/stg_orders.sql
{{ config(materialized='view') }}

SELECT
    id AS order_id,
    customer_id,
    order_date,
    CAST(total AS DECIMAL(10,2)) AS total_amount
FROM {{ source('raw', 'orders') }}
WHERE order_date >= '2023-01-01'
```

## Data Quality

```python
def validate_data(df):
    assert df['order_id'].is_unique, "Duplicate IDs"
    assert df['amount'].ge(0).all(), "Negative amounts"
    assert df['customer_id'].notna().all(), "Null customers"
```

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [christopherlouet](https://github.com/christopherlouet)
- **Source:** [christopherlouet/claude-base](https://github.com/christopherlouet/claude-base)
- **License:** MIT
- **Homepage:** https://christopherlouet.github.io/claude-base/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-christopherlouet-claude-base-data-pipeline
- Seller: https://agentstack.voostack.com/s/christopherlouet
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.