Enhance your AI development workflow with expert guidance on crafting effective prompts for large language models. This skill acts as a conversational consultant, leading you through a structured four-phase process—Intake, Analysis, Recommendation, and Construction—to build prompts that are clear, cost-efficient, and high-performing. Whether you are dealing with simple classification or complex multi-step reasoning, it leverages a library of advanced patterns like Chain-of-Thought, Tree-of-Thought, and Few-shot prompting to ensure your LLM interactions are reliable and optimized for production environments.
Key Features
01Performance troubleshooting to identify and fix ambiguous instructions or poor structure
020 GitHub stars
03Structured four-phase conversational workflow for prompt development
04Cost-aware optimization strategies to balance performance with token usage
05Decision framework for selecting techniques like Chain-of-Thought and Self-consistency
06Comprehensive library of ready-to-adapt templates for common AI tasks
