Can I use these patterns for production RAG systems?

Yes, the skill includes specific patterns for Retrieval-Augmented Generation (RAG), focusing on context utilization, citation, and handling cases where information is missing.

What are prompt engineering patterns?

Prompt engineering patterns are standardized, reusable techniques like Chain-of-Thought and few-shot learning used to systematically improve the accuracy, reasoning, and consistency of LLM responses.

What is dynamic few-shot example selection?

It is a technique where the system uses vector embeddings to find and inject the most relevant examples into a prompt based on the user's specific query, rather than using a static set of examples.

How does this skill help with structured data?

It provides specific implementation patterns for using Pydantic schemas and JSON mode, ensuring that the AI returns data in a predictable, type-safe format that your code can easily parse.

Prompt Engineering Patterns

Name: Prompt Engineering Patterns
Author: rajasekarm

byrajasekarm

0•

Ciencia de Datos y ML

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production.

This skill provides a comprehensive library of advanced prompt engineering patterns designed to elevate LLM outputs from basic responses to production-grade results. It covers essential strategies like Few-Shot Learning with dynamic example selection, Chain-of-Thought reasoning for complex logic, and Pydantic-backed structured outputs for reliable system integration. Whether you are optimizing system prompts, building RAG-augmented applications, or implementing error-recovery loops, these patterns offer proven architectural blueprints to ensure your AI applications are consistent, cost-effective, and highly controllable.

Características Principales

01Progressive disclosure and iterative prompt optimization workflows

02Type-safe structured output enforcement via Pydantic and JSON mode

03Dynamic few-shot example selection using semantic similarity

04Implementation of Chain-of-Thought (CoT) and self-verification reasoning

050 GitHub stars

06System prompt design patterns for specialized AI personas

Casos de Uso

01Building scalable RAG systems with high-precision context utilization

02Designing reliable extraction pipelines for unstructured data into validated JSON

03Improving reasoning capabilities for complex coding, logic, or mathematical tasks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add rajasekarm/skills prompt-engineering-patterns

For use in Claude.ai and ChatGPT

Download Skill