skills.rest
gatovillano
gatovillanoCOMMUNITY
Explore all skills by this author →
GitHub

retrieval-augmented-generation

Retrieve user-specific information via semantic search and knowledge graph analysis.

Updated Jun 19, 2025
Search Tags:#RAG#knowledge-graph#semantic-search#knowledge-retrieval#AI-assisted-research
One-click install
npx skills add https://github.com/gatovillano/KognitoAI --skill retrieval-augmented-generation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: retrieval-augmented-generation
Source: https://github.com/gatovillano/KognitoAI/tree/main/skills/rag_skill
Command: npx skills add https://github.com/gatovillano/KognitoAI --skill retrieval-augmented-generation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PostgreSQL, pgvector, Neo4j, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill solves the challenge of accessing specific user information, in-depth context, and relationship analysis within a knowledge base, providing comprehensive information retrieval through RAG (Retrieval Augmented Generation).

Core Features & Use Cases

  • Semantic Search: Allows for searching within the knowledge base using natural language, leveraging pgvector for semantic similarity.
  • Knowledge Graph Navigation: Enables exploration of conceptual relationships and in-depth analysis of user's knowledge graph.
  • Scoped Analysis: Focuses on specific user content or documents for tailored searches.
  • Multi-source Retrieval: Combines results from various knowledge sources for a holistic view.
  • Confidence Scoring: Evaluates the relevance of search results.
  • Use Case: When a user needs to find specific information from their notes, documents, or the knowledge graph, or when the context of a user's projects needs to be analyzed.

Quick Start

Use the retrieval-augmented-generation skill to find related notes and documents about "machine learning project" in your workspace.

Frequently Asked Questions about retrieval-augmented-generation

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

FAQPage Schema
How does semantic search with RAG enhance knowledge retrieval?▼

Knowledge graph navigation in RAG allows you to explore conceptual relationships and analyze connections between user notes and documents, providing in-depth context for project analysis.

How do I set up retrieval augmented generation for a personal knowledge base?▼

To set up RAG for personal knowledge management, you need PostgreSQL with the pgvector extension for semantic search and a Neo4j knowledge graph to map and navigate conceptual relationships.

Does retrieval augmented generation work without Neo4j and PostgreSQL pgvector?▼

No, this RAG implementation requires PostgreSQL with the pgvector extension to perform semantic similarity searches and a Neo4j database to enable knowledge graph navigation and relationship analysis.

What is the best way to combine semantic search with knowledge graph analysis?▼

The best way to combine semantic search with knowledge graph analysis is using a RAG architecture that leverages pgvector for semantic similarity retrieval and Neo4j for relationship mapping, yielding multi-source results with confidence scoring.

Can I scope semantic search to specific documents for project context analysis?▼

Yes, you can scope semantic search to specific user content or documents, enabling tailored project context analysis and focused information retrieval within your personal knowledge management system.

Related Skills

an8079an8079
4

graph-rag

Build and query Neo4j knowledge graphs with SPARQL for RAG systems.

Community
Advanced
thecloudtipsthecloudtips
18

Answer Synthesis

Synthesize sourced answers with inline citations and confidence ratings.

Community
Advanced
ZpankzZpankz
7

limitless-cli

Query Limitless Pendant lifelogs and chats via FalkorDBLite semantic search.

Community
Advanced
kryptodoggkryptodogg

Cipher Data Engineer Skill

Manage data encoding, serialization, and Neo4j/Qdrant database integration.

Community
Advanced