context-engineering

Data transformation framework for AI. Ultra performant, with incremental processing.

🔥 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.

The complete Agentic Context Engineering Foundation for building AI-native companies. Orchestrate LLMs with APIs or private deployments with context automation using your data. Run anywhere - local, cloud, or bare metal.

Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations

🧠🔗 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

🧠 Context Engineering Research - Not just another agent collection, but using research and context engineering to function as a collective. Hub-and-spoke coordination through Claude Code.

In the midst of all the tools out there that you can possibly use to keep track of them. Here's a "shovel" that just works to try them all out.

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

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

A minimalist MVP demonstrating a simple yet profound insight: aligning AI memory with human episodic memory granularity. Shows how this single principle enables simple methods to rival complex memory frameworks for conversational tasks.

The Keystone Framework for AI-Driven Code ! Turn any AI coding assistant into a disciplined, project-aware engineering partner that respects your architecture and coding standards

🚀 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.

practical claude code commands and sub-agents

Implementation of contextual engineering pipeline with LangChain and LangGraph Agents

A curated collection of resources, papers, tools, and best practices for Context Engineering in AI agents and Large Language Models (LLMs).

ContextX: Context-driven AI development framework powered by Claude Code. Transform documents into complete projects with intelligent agent workflows.

Standardized, reusable LLM instructions for Smart Contract Auditing

AI-powered file organization and context engineering that understands content, not patterns. Automatically sorts temporary scripts from permanent docs while preserving your workflow. Works seamlessly with Claude Code hooks. Protects README, LICENSE, configs.

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.

🧬 KIP is a Knowledge-memory Interaction Protocol designed for LLMs, aiming to build a sustainable learning and self-evolving memory system for AI Agents.