🧠🔗 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.

Submodular optimization for context engineering: query fan-out, text selection, passage reranking

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

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!

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.

🚀 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

Context optimization for agentic workflows. Extract and format code changes with surgical precision for LLM.

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.

eLLM provides million-token inference on CPUs

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

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.

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.

Direct AI agents to build production apps at unprecedented speed with this edge-first Next.js + Convex + Cloudflare starter template designed for agentic development workflows.

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

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