How does Few-Shot Learning improve model behavior?

By providing 2-5 examples of desired behavior, it teaches the model specific formatting and reasoning patterns through demonstration rather than just text instructions.

When should I use the Prompt Engineering skill?

Use this skill when you need to improve model consistency, reduce token usage, or debug unexpected agent behaviors and edge cases in your AI workflows.

What is the benefit of Chain-of-Thought prompting?

It improves accuracy on complex analytical tasks by 30-50% by requesting step-by-step reasoning before the final answer, allowing the model to process logic more reliably.

What is the recommended Instruction Hierarchy?

The optimal hierarchy follows a structure of System Context, followed by Task Instruction, Examples, Input Data, and finally the desired Output Format.

Prompt Engineering Expert

Name: Prompt Engineering Expert
Author: claudiodearaujo

byclaudiodearaujo

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Data Science & ML

Optimizes LLM performance and reliability through advanced prompting patterns, few-shot learning, and structured chain-of-thought techniques.

This skill transforms Claude into a specialized prompt engineering consultant, providing a comprehensive framework for designing, testing, and refining AI prompts. It offers deep insights into advanced techniques like few-shot learning and chain-of-thought prompting to improve model accuracy, alongside modular template systems and system prompt design for consistent, production-grade outputs. Whether you are debugging agent behavior or scaling AI workflows, this skill provides the patterns and best practices needed to ensure your prompts are cost-effective, reliable, and highly controllable.

Key Features

01Chain-of-Thought reasoning patterns for complex logical tasks

02Systematic prompt optimization and A/B testing strategies

031 GitHub stars

04Implementation of Few-Shot Learning with optimized input-output pairs

05Advanced system prompt architecture for global behavior constraints

06Reusable template systems for modular and consistent prompt design

Use Cases

01Standardizing AI output formats for production API integrations

02Debugging and fixing inconsistent agent behaviors or edge case failures

03Improving model accuracy for complex analytical or mathematical tasks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claudiodearaujo/sistema-de-narra-o-de-livro prompt-engineering

For use in Claude.ai and ChatGPT

Download Skill