Repository History
10 repositories tagged with AI Development
Loop Library: Practical Repeatable AI-Agent Workflows
The Loop Library is a GitHub repository offering reusable AI agent workflows for various domains like engineering, content, and design. It introduces the concept of "loops," which are structured, repeatable instructions that guide AI agents through multi-step tasks. This skill enables agents to learn from results, adapt, and complete complex tasks more reliably than with one-shot prompts.
agency-agents: Your Complete AI Agency of Specialized Experts
agency-agents offers a comprehensive collection of over 140 meticulously crafted AI agent personalities, designed to act as specialized experts across various domains. From frontend development to marketing and sales, each agent comes with a unique voice, proven processes, and deliverable-focused outcomes. This repository provides a ready-to-deploy AI dream team to transform your workflow and accelerate project delivery.
get-shit-done: Streamlining AI-Powered Development with Meta-Prompting and Context Engineering
get-shit-done is a robust, lightweight system designed to enhance AI-powered development, particularly with Claude Code. It tackles challenges like context degradation through advanced meta-prompting and context engineering. This tool enables developers to build high-quality software efficiently, transforming ideas into reliable code with structured workflows.
Oh-My-ClaudeCode: Teams-First Multi-Agent Orchestration for Claude Code
Oh-My-ClaudeCode is a powerful GitHub repository that provides teams-first multi-agent orchestration for Claude Code, enhancing its capabilities with zero learning curve. It enables developers to build, refactor, and verify code efficiently through intelligent automation and parallel execution. This tool aims to supercharge your Claude Code experience, making complex development tasks simpler and more cost-effective.
GenAIScript: Automatable GenAI Scripting with TypeScript/JavaScript
GenAIScript is an open-source project from Microsoft that enables programmatic assembly of prompts for Large Language Models (LLMs) using JavaScript and TypeScript. It allows developers to orchestrate LLMs, tools, and data directly in code, streamlining the development of GenAI applications. This framework offers seamless Visual Studio Code integration and a flexible command-line interface for efficient GenAI scripting.
Agentrooms: Multi-Agent Claude Code Orchestration Desktop App
Agentrooms is a desktop application and API designed for multi-agent Claude Code orchestration. It enables users to coordinate both local and remote agents through an intuitive @mentions system, streamlining complex development workflows. This tool facilitates collaborative development by routing tasks to specialized agents, all while leveraging your existing Claude subscription without requiring additional API keys.
cursor-memory-bank: Structured AI Development Workflow with Cursor 2.0 Commands
cursor-memory-bank is a modular, documentation-driven framework designed to enhance AI-assisted development within the Cursor editor. It leverages Cursor 2.0 commands to provide persistent memory and guide AI through a structured development workflow. This system uses visual process maps and token optimization to streamline tasks from initialization to archiving.
Laravel Claude Code Setup: AI-Powered Development for Laravel with Figma Integration
This repository provides a one-command setup for integrating Claude Code with your Laravel development. It automatically configures various MCP servers, enabling AI-powered features like GitHub integration, database access, and a powerful new Figma design-to-code workflow. This streamlines the development process, allowing developers to leverage AI for tasks from code generation to design system extraction.
Rig: Build Modular and Scalable LLM Applications in Rust
Rig is a powerful Rust library designed for building modular, scalable, and ergonomic LLM-powered applications. It offers extensive features, including agentic workflows, compatibility with over 20 model providers, and seamless integration with more than 10 vector stores. Developers can leverage Rig to create robust generative AI solutions with minimal boilerplate.
quarkus-langchain4j-workshop: Build AI-Infused Apps with Quarkus and LangChain4j
Explore the `quarkus-langchain4j-workshop` to learn how to develop AI-infused applications using Quarkus and LangChain4j. This workshop provides a structured approach, guiding you through various steps to build powerful AI solutions. It's an excellent resource for developers looking to integrate large language models into their Quarkus projects.