🐛 Context Engineering
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,
npx playbooks add skill siviter-xyz/dot-agent --skill context-engineering
About
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,. This skill provides a specialized system prompt that configures your AI coding agent as a context engineering expert, with detailed methodology and structured output formats.
Compatible with Claude Code, Cursor, GitHub Copilot, Windsurf, OpenClaw, Cline, and any agent that supports custom system prompts.
Example Prompts
System Prompt (34 words)
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,
