prorag-developer

Scaffold and customize ProRAG projects with custom pipeline steps.

Updated Aug 23, 2026

Search Tags:#development #llm #rag #customization #pipeline #provrag

Ready to run

npx skills add https://github.com/diegouis/provectus-marketplace --skill prorag-developer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prorag-developer
Source: https://github.com/diegouis/provectus-marketplace/tree/main/plugins/proagent-prorag/skills/prorag-developer
Command: npx skills add https://github.com/diegouis/provectus-marketplace --skill prorag-developer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the development and customization of Retrieval Augmented Generation (RAG) applications, enabling efficient creation and deployment of AI-powered knowledge systems.

Core Features & Use Cases

Scaffolding: Quickly initialize new ProRAG projects with best practices.
Pipeline Customization: Modify ingestion and RAG pipelines for specific data sources and retrieval strategies.
Configuration & Operation: Manage settings, LLM providers, and operational commands for RAG applications.
Use Case: A developer needs to build a RAG application to answer questions about internal company documentation. They use this Skill to scaffold the project, customize the ingestion pipeline to handle various document types, and configure the retrieval to use OpenSearch.

Quick Start

Use the prorag-developer skill to scaffold a new ProRAG project.

Frequently Asked Questions about prorag-developer

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

FAQPage Schema

How do I build and customize a RAG application pipeline?▼

To build and customize a RAG application pipeline, you can scaffold a new project and modify the ingestion and retrieval processes to handle specific data sources and strategies. This enables efficient creation of AI-powered knowledge systems.

What is the best way to initialize a new RAG project with best practices?▼

The best way to initialize a new RAG project is by scaffolding it with predefined structures. This sets up the foundational pipeline composition, data models, and LLM protocols for your application.

Can I modify the ingestion pipeline to handle various document types for RAG?▼

Yes, you can modify the ingestion pipeline to handle various document types for RAG. The customization features allow you to adjust data models and retrieval mechanisms for specific documentation sources.

How do I configure LLM providers and manage the RAG lifecycle via CLI?▼

You can configure LLM providers and manage the RAG lifecycle through CLI operations. This includes managing application settings, operational commands, and deployment configurations for your retrieval augmented generation system.

Does this RAG development approach support configuring retrieval to use OpenSearch?▼

Yes, this RAG development approach supports configuring retrieval to use OpenSearch. You can customize the retrieval mechanisms within the pipeline to integrate with your chosen search providers and data sources.