rag-retrieval
✓Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
Installation
SKILL.md
Combine vector search with LLM generation for accurate, grounded responses.
| Top-k | 3-10 documents | | Temperature | 0.1-0.3 (factual) | | Context budget | 4K-8K tokens | | Hybrid ratio | 50/50 semantic/keyword |
retrieval-patterns Keywords: retrieval, context, chunks, relevance Solves:
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search. Source: yonatangross/orchestkit.
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/yonatangross/orchestkit --skill rag-retrieval- Source
- yonatangross/orchestkit
- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-01
- Updated
- 2026-02-18
Quick answers
What is rag-retrieval?
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search. Source: yonatangross/orchestkit.
How do I install rag-retrieval?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/yonatangross/orchestkit --skill rag-retrieval Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/yonatangross/orchestkit
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-01