tool-design

Context Engineering skills for building production-grade AI agent systems

A comprehensive collection of agent skills focused on context engineering principles for building production-grade AI agent systems, covering context management, multi-agent architectures, memory systems, and evaluation frameworks.

A collection of agent skills focused on context engineering principles, teaching the art of curating the language model's context window for building production-grade AI agent systems.

Context engineering skills collection teaching the art of curating LLM context windows for production-grade AI agent systems, covering system prompts, tool definitions, and message history management

A context engineering skill that teaches agents how to compress and manage context windows efficiently, addressing attention mechanics, the lost-in-the-middle phenomenon, and token budget optimization for production AI systems.

A comprehensive collection of agent skills focused on context engineering principles for building production-grade AI agent systems. It covers managing context windows through attention mechanics, token budgeting, and structured information curation, and has been cited in academic research from Peking University and multiple US universities.

A comprehensive collection of agent skills focused on context engineering principles for building production-grade AI agent systems. Covers context fundamentals, degradation patterns, compression strategies, multi-agent architectures, memory systems, and tool design, cited in academic research from Peking University and CMU.

A comprehensive collection of agent skills focused on context engineering and harness engineering for building production-grade AI agent systems, covering context fundamentals, compression, multi-agent patterns, and memory system design. Cited in academic research from Peking University and CMU.

Part of Agent Skills for Context Engineering, a collection focused on context engineering and harness engineering principles for building production-grade AI agent systems, cited in academic research from Peking University and others.

A collection of agent skills focused on context engineering principles for building production-grade AI systems, covering context window management, attention mechanics, compression strategies, multi-agent patterns, and context degradation prevention.