🧠🔗 From idea to production in just few lines: Graph-Based Programmable Neuro-Symbolic LM Framework - a production-first LM framework built with decade old Deep Learning best practices

🔥 Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents.

ApeRAG: Best choice for building your own Knowledge Graph and for Context Engineering

Give Copilot a memory! MemoriPilot provides seamless, persistent context management that makes Copilot aware of your project decisions, progress, and architectural patterns - dramatically improving the relevance and quality of AI assistance.

Context engineering is the new vibe coding – it’s how to actually make AI coding assistants work. Gemini CLI is the best for this, and this repo is based on the coleam00 template made for Claude Code!

🚀 A framework for Context Engineering using Google Gemini. Move beyond simple prompting and learn to systematically provide context to your AI coding assistant for more reliable, consistent, and complex software development.

A comprehensive collection of prompts, strategies, and best practices for effectively utilizing large language models (LLMs).

🚀 Browser-based tool for creating reusable sets of context for LLM. Improve response quality & time and reduce token usage. Privacy-first, works with any LLM (Claude, GPT-4, Gemini). Stop re-explaining your codebase to AI (and your team members).

Angular TypeScript template demonstrating context engineering for AI-assisted development. Features Domain-Driven Design (DDD), SOLID principles, and PRP workflow for generating high-quality code with structured AI guidance.

Intelligent Context Engineering Assistant for Multi-Agent Systems. Analyze, optimize, and enhance your AI agent configurations with AI-powered insights

A lightweight, conversational AI assistant powered by a reasoning agent. This project provides a simple framework for building and running your own AI assistant from the command line.

Yudai is a context-engineered coding agent that connects to your GitHub repo and turns curated chat summaries, file-dependency insights, and analytics into smart context cards. One click spins those cards into complexity-scored issues, auto-tested code patches, and a labeled pull request with an inline diff viewer so you can merge with confidence.

A comprehensive Model Context Protocol (MCP) server designed to manage AI agent handoffs with structured documentation, progress tracking, and seamless task transitions between agents. Supports HTTP streaming.

Context Engineering - The art of providing all the context for the task to be plausibly solvable by the LLM.

eLLM provides million-token inference on CPUs

Template for AI-maintained documentation that gives agents an always up-to-date project context.

A small application to create a map of any repository for use by LLMs and Agents.

RAGflow at Claude Desktop - for expert knowledge base access based of complex documents

JabbarRoot AI extension transforms ideas into structured software artifacts (code, docs) via intelligent workflows. It optimizes context for LLMs, manages complexity, and industrializes development for augmented software cognition.

A curated list of tools, frameworks, and platforms to build powerful LLM applications through effective context engineering.