OpenAI Prompt Engineer

About

Empowers developers and AI engineers to craft, analyze, and refine prompts tailored for high-performance models like OpenAI’s GPT-5 and Anthropic’s Claude. By applying systematic frameworks such as role-based context, XML tag structuring, and progressive disclosure, the skill ensures consistent, accurate, and cost-effective AI outputs. Whether building complex agentic workflows or simple data extraction tasks, it provides actionable guidance and model-specific optimizations to maximize instruction following and minimize unpredictable behavior.

Key Features

• Provides model-specific optimizations for GPT-5 reasoning and Claude XML structuring
• Applies structured formatting templates including roles, constraints, and output specifications
• 6 GitHub stars
• Guides progressive disclosure workflows for complex, multi-step tasks
• Analyzes existing prompts to identify weaknesses and suggest quality improvements
• Implements advanced prompting patterns like Chain-of-Thought and few-shot learning

Use Cases

• Standardizing prompt structures across a development team for predictable model behavior
• Designing complex agentic workflows that require high reasoning effort and strict adherence to logic
• Refining inconsistent prompts to improve accuracy and reduce token usage or latency