Optimizes AI agent performance through structured XML system prompts, clear instruction hierarchies, and high-quality few-shot examples.
This skill provides a comprehensive framework for creating production-grade system prompts for AI agents, specifically optimized for Claude's reasoning capabilities. It enforces a mandatory XML tagging structure to improve model comprehension and maintainability, while offering standardized patterns for role definition, hierarchical instructions, and tool usage. By implementing these best practices, developers can significantly increase agent reliability, reduce instruction-following errors, and ensure consistent output formats across complex AI workflows.
주요 기능
010 GitHub stars
02Comprehensive role definition templates for specific domain expertise and communication styles
03Explicit tool usage guidance and error handling constraints for agent safety
04Standardized few-shot example patterns to establish high-quality response benchmarks
05Hierarchical instruction frameworks covering analysis, planning, and execution phases
06Mandatory XML tag structuring for superior model parsing and boundary recognition
사용 사례
01Standardizing prompt templates across a team to ensure consistent AI performance
02Developing specialized system prompts for technical AI agents and microservices
03Refining agent behavior to improve adherence to complex multi-step instructions
