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rag-expert

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Build robust RAG systems with reliable retrieval.

Software Engineering#semantic search#embeddings#rag#retrieval#vector search#chunking#reranking
Authorgonzoblasco
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps teams design and implement production‑grade Retrieval‑Augmented Generation (RAG) pipelines by unifying semantic search, keyword matching, and reranking to improve answer quality and reliability.

Core Features & Use Cases

  • Hybrid Retrieval: Combine vector-based semantic search with keyword matching to handle concepts, codes, and identifiers.
  • Reranking & Evaluation: Apply reranking to surface the most relevant results before generation, with lightweight evaluation templates.
  • Reusable Architecture: Provides chunking, indexing, and evaluation templates to accelerate AI app delivery across domains.

Quick Start

Configure a minimal RAG workflow against a small document set using semantic chunking and a hybrid retriever, then run a simple QA prompt.

Dependency Matrix

Required Modules

None required

Components

references

đź’» Claude Code Installation

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Please help me install this Skill:
Name: rag-expert
Download link: https://github.com/gonzoblasco/antigravity-developer-stack/archive/main.zip#rag-expert

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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