What is a GrepAI workspace?

A GrepAI workspace is a configuration that groups multiple code projects together using a shared vector store and embedding model, allowing for semantic search across all included projects simultaneously.

Which vector backends are supported?

This skill supports Qdrant (a lightweight, purpose-built vector database) and PostgreSQL with the pgvector extension.

How do I know if my projects are finished indexing?

You can use the 'status' operation to view the number of files and chunks indexed for each project, along with a health indicator (OK, FAIL, or STALE).

Can I use this skill for private, offline development?

Yes. By selecting Ollama as your embedding provider during workspace creation, you can index and search your code without sending data to cloud services like OpenAI.

Does deleting a workspace remove my source code?

No. Deleting a workspace only removes the GrepAI configuration and the associated vector index; your original source code files are never modified or deleted.

GrepAI Workspace Manager

Name: GrepAI Workspace Manager
Author: jugrajsingh

byjugrajsingh

0•

데이터 과학 및 ML

Manage GrepAI semantic search workspaces including creation, project management, and indexing status monitoring.

The GrepAI Workspace Manager skill provides a streamlined interface for organizing complex codebases into searchable semantic units. It simplifies the setup of cross-project semantic search by guiding users through the configuration of vector backends like Qdrant or PostgreSQL and embedding providers such as Ollama or OpenAI. From initializing new workspaces with specific embedding models to managing background watchers and verifying indexing health, this skill automates the technical overhead of maintaining a high-performance local RAG (Retrieval-Augmented Generation) system for your development environment.

주요 기능

01Comprehensive project lifecycle management for adding, removing, and listing indexed directories

02Automated health checks for Docker-based backends (Qdrant, Postgres) and local API endpoints

030 GitHub stars

04Background watcher management to ensure semantic indices remain synchronized with code changes

05Interactive workspace creation with guided backend and embedding provider selection

06Detailed status reporting for indexing progress, file counts, and chunking statistics

사용 사례

01Configuring a private, local-first code search tool using Ollama and Qdrant for sensitive enterprise data

02Troubleshooting stale search results by auditing workspace indexing health and watcher status

03Setting up a unified semantic search index across multiple related microservices for easier navigation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jugrajsingh/skillgarden workspace-managing

For use in Claude.ai and ChatGPT

Download Skill