xs:workspace-rag

What problem does it solve?

This Skill addresses the challenge of finding specific information scattered across numerous files within a large project or personal workspace, which can be time-consuming and inefficient with traditional search methods.

Core Features & Use Cases

• Vector Search: Utilizes a lightweight embedding model (multilingual-e5-small) and SQLite for efficient semantic search across various file types.
• R²AG Integration: Implements a simplified version of R²AG to provide relevance scores, helping LLMs prioritize information.
• Fast Updates: Supports differential indexing to quickly update the search index when files change.
• Use Case: You need to recall details about a specific feature you implemented months ago. Instead of manually searching through code files, markdown notes, and documentation, you can ask the AI to "find information about the user authentication module," and it will quickly return the most relevant snippets with confidence scores.

Quick Start

Ask the AI to search your workspace for "recent project updates".