What makes this prompt engineering skill unique?

Unlike generic AI advice, this skill delivers production-ready, model-optimized prompts and uses progressive disclosure to ensure the final output perfectly matches your specific use case.

Can it optimize prompts for models other than Claude?

Yes, while optimized for Claude's XML and long-context capabilities, it includes dedicated frameworks for GPT models, focusing on function calling and JSON schema adherence.

How does it handle complex multi-agent requirements?

It uses a structured approach to define roles, clear behavioral guidelines, and decision frameworks, making it ideal for designing multi-agent orchestration systems.

Does it provide examples with the prompts?

Yes, it follows a 'Show, Don't Tell' philosophy, providing 2-4 few-shot examples and structured templates to ensure the LLM understands the desired behavior.

Prompt Engineering Expert

Name: Prompt Engineering Expert
Author: theMickster

bytheMickster

数据科学与机器学习

Crafts production-ready LLM prompts, agent definitions, and system instructions optimized for Claude and GPT models.

关于

The Prompt Engineering skill transforms Claude into a specialized prompt architect capable of designing complex multi-agent orchestrations, system prompts, and custom skill templates. By leveraging advanced techniques like Chain-of-Thought reasoning, XML-structured output, and progressive disclosure, it ensures that every prompt is high-performing, model-optimized, and ready for immediate production deployment. Whether you are kickstarting a new AI project or refining existing logic to reduce hallucinations, this skill provides the rigorous framework needed for professional-grade AI behavior.

主要功能

Generates production-ready system prompts and agent definitions for multi-agent workflows.
Optimizes existing prompts using model-specific architectures like XML for Claude and JSON mode for GPT.
Implements advanced reasoning patterns including Chain-of-Thought and Few-Shot learning.
0 GitHub stars
Includes built-in verification steps to ensure prompts handle edge cases and ethical constraints.
Utilizes progressive disclosure to gather critical context before crafting technical solutions.

使用场景

Designing specialized Claude Code skills and system-level instructions for autonomous agents.
Creating complex prompt templates for automated content generation and data extraction.
Refining underperforming prompts to improve output accuracy and structural consistency.

关于

主要功能

Generates production-ready system prompts and agent definitions for multi-agent workflows.
Optimizes existing prompts using model-specific architectures like XML for Claude and JSON mode for GPT.
Implements advanced reasoning patterns including Chain-of-Thought and Few-Shot learning.
0 GitHub stars
Includes built-in verification steps to ensure prompts handle edge cases and ethical constraints.
Utilizes progressive disclosure to gather critical context before crafting technical solutions.

使用场景

Designing specialized Claude Code skills and system-level instructions for autonomous agents.
Creating complex prompt templates for automated content generation and data extraction.
Refining underperforming prompts to improve output accuracy and structural consistency.