Optimize AI Retrieval: Build Your RAG Pipeline Now

Optimize AI Retrieval: Build Your RAG Pipeline Now

This AI agent skill facilitates the construction of retrieval-augmented generation (RAG) pipelines over your proprietary documents. It includes capabilities such as structure-aware chunking, pinned embeddings in pgvector, and hybrid vector plus full-text search with Reciprocal Rank Fusion (RRF) for enhanced query precision and tenant isolation. The skill also supports retrieval evaluations before initiating prompt tuning for improved accuracy in AI-generated answers.

What this skill does

• Ingest and normalize data from your documents.
• Perform structure-aware chunking to optimize data retrieval.
• Embed data using pinned embeddings stored in pgvector.
• Implement hybrid vector and full-text search with RRF.
• Ensure tenant isolation during query execution.
• Provide retrieval evaluations (recall@k, MRR) prior to prompt tuning for refined response accuracy.
• Generate answers with citations, incorporating an "I don't know" path for uncertain queries.

Who it is for

This skill is tailored for developers and teams utilizing AI coding agents, such as Claude Code, Cursor, and Codex. It is particularly beneficial for those who require detailed retrieval systems to enhance AI interactions with proprietary data.

Use cases

• Building sophisticated document retrieval systems for customer support applications.
• Developing internal knowledge bases that require precision retrieval and citation.
• Enhancing AI applications that rely on structured document analysis and answer generation.

Technical details

• Utilizes pgvector as the default storage mechanism for embeddings.
• Employs hybrid search mechanisms, combining vector search with full-text RRF-based methods.
• Integrates tenant isolation to ensure secure and separate query processing.
• Supports manual retrieval evaluation measures like recall@k and Mean Reciprocal Rank (MRR).
• Relies on understanding and mapping existing vector schemas and retrieval code through grep-based audits.

Source & Licence

This package is built on open-source work published by VelimirMueller (VelimirMueller/claude-skills) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.