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pipeline-builder

Create a minimal pipeline in the given format.

Updated Jan 20, 2026
Search Tags:#automation#workflow#ETL#pipeline#Python#data-processing#OpenHEXA
One-click install
npx skills add https://github.com/BLSQ/mcp_servers --skill pipeline-builder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pipeline-builder
Source: https://github.com/BLSQ/mcp_servers/tree/main/.claude/skills/pipeline-builder
Command: npx skills add https://github.com/BLSQ/mcp_servers --skill pipeline-builder

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

OpenHEXA pipeline design and automation can be complex; this Skill guides users to quickly configure end-to-end data pipelines without starting from scratch.

Core Features & Use Cases

  • Template-driven development: Start from curated examples and adapt them to your data workflows.
  • Declarative pipeline design: Define steps, parameters, and outputs with clear structure for reproducible results.
  • Use Case: Create a reusable ETL pipeline to extract from a source, transform data, and load into a workspace database.

Quick Start

Create a minimal OpenHEXA pipeline named 'demo-pipeline' that reads from a sample source, runs a simple task, and writes results to a file.

Frequently Asked Questions about pipeline-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an ETL pipeline in OpenHEXA for data processing?▼

Yes, you can design declarative OpenHEXA pipelines to handle reproducible data workflows by defining steps, parameters, and outputs with a clear structure, ensuring consistent results across data engineering tasks.

Can I use Python decorators to automate OpenHEXA workflow tasks?▼

Yes, you can use Python decorators to define and automate OpenHEXA workflow tasks, leveraging the OpenHEXA toolbox for end-to-end pipeline automation and structured file or database I/O operations.

What is the best way to configure file and database I/O in a Python data pipeline?▼

The best way to configure file and database I/O in a Python data pipeline is using OpenHEXA's declarative design, which provides curated examples and connections to read from sources and write results reproducibly.

Do I need prior knowledge of OpenHEXA architecture to start automating data workflows?▼

No, you do not need extensive prior knowledge of OpenHEXA architecture to automate data workflows, as the skill provides template-driven examples to quickly configure end-to-end pipelines without starting from scratch.

Why should I use declarative pipeline design for data engineering instead of manual scripting?▼

You should use declarative pipeline design because it ensures reproducible data workflows by clearly defining steps, parameters, and outputs, avoiding the complexity and inconsistency of manual scripting for data engineering tasks.

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