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Rag Pipeline Builder

Checked
patricio0312rev·vlatest·ai-ml·MIT

Automates building Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval and AI application development.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add patricio0312rev/skills --skill rag-pipeline-builder -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

patricio0312rev

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Install target

Live repository

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No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

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  • Pinned to a commit: passed

    Scanned patricio0312rev/skills at 79ea6af485.

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Commit
79ea6af485
Manifest
ai-engineering/rag-pipeline-builder/SKILL.md
Scanned
1 file, 227 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

The RAG Pipeline Builder skill automates the creation of Retrieval-Augmented Generation workflows, allowing AI agents to dynamically construct pipelines that fetch external data before generating responses. It streamlines the setup of complex retrieval chains without requiring manual code configuration for every new use case.

When to use it

  • Rapidly prototype document-based Q&A systems for internal knowledge bases.
  • Build dynamic search agents that query live databases or APIs before answering user queries.
  • Automate the deployment of multi-step retrieval strategies across different data sources.
  • Test and validate RAG architectures quickly during the development phase.

Key capabilities

  • Automated pipeline construction for Retrieval-Augmented Generation tasks.
  • Dynamic integration with external data sources for context enrichment.
  • Streamlined workflow generation without manual coding overhead.
  • Support for complex retrieval chains to improve answer accuracy.

Example prompts

  • "Create a RAG pipeline that retrieves relevant documents from my uploaded PDFs before answering questions."
  • "Build an agent workflow that searches a live database and generates a summary report based on the results."
  • "Set up a multi-step retrieval chain to fetch data from three different APIs and synthesize a final response."

Tips & gotchas

Ensure your external data sources are properly accessible and authenticated before attempting to build pipelines that rely on them. This skill is best suited for developers looking to accelerate RAG implementation rather than fine-tune low-level model parameters.