# Context Engineering

> Master context engineering for AI agent systems.

Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.

- Page: https://ss33.ai/skills/mrgoonie/context-engineering-41616878566
- Publisher: mrgoonie
- Category: [AI & Agents](https://ss33.ai/skills/category/ai-and-agents-y6jz7i) › [Memory & context](https://ss33.ai/skills/category/ai-and-agents-y6jz7i/memory-and-context-5m28a5)
- Source: https://github.com/mrgoonie/claudekit-skills/blob/80113d86bc4407f105af40a2c4ea58194f7c370a/.claude/skills/context-engineering/SKILL.md

## Skill

This skill's licence does not allow redistribution, so the store does not serve its text. Get it from the author: https://github.com/mrgoonie/claudekit-skills/blob/80113d86bc4407f105af40a2c4ea58194f7c370a/.claude/skills/context-engineering/SKILL.md