Context Engineering

This is the skill you need when your agent hits token limits or starts forgetting things mid-conversation. It covers the full stack: fundamentals like attention mechanics and the U-shaped attention curve, practical optimization techniques like compaction and caching, memory architectures for cross-session persistence, and multi-agent patterns for isolating context. The four-bucket strategy (write, select, compress, isolate) is clean. Ships with analyzer scripts and specific metrics like triggering compaction at 70-80% utilization. Honest take: if you're building anything more complex than a simple chatbot, you'll eventually need this. The evaluation section using LLM-as-Judge is especially useful for measuring whether your optimizations actually work.