Can I use these patterns for RAG applications?

Absolutely. It includes specific integration patterns for Retrieval-Augmented Generation to ensure the model stays grounded in provided context.

What is Chain-of-Thought prompting?

Chain-of-Thought (CoT) is a technique that encourages the model to generate intermediate reasoning steps, significantly improving performance on complex logic and math tasks.

Does this skill support structured data formats?

Yes, it includes advanced patterns for JSON mode, Pydantic schema enforcement, and type-safe response handling for easy integration with backend code.

What are the benefits of using these prompt patterns?

These patterns increase the reliability, accuracy, and controllability of LLM outputs while reducing non-deterministic errors in production environments.

Prompt Engineering Patterns

Name: Prompt Engineering Patterns
Author: sla-te

bysla-te

0•

데이터 과학 및 ML

Implements advanced prompt engineering techniques to maximize LLM reliability, reasoning capabilities, and structured output quality.

This skill provides a comprehensive framework of industry-standard prompt engineering patterns designed to enhance the performance and controllability of Large Language Models in production environments. It equips developers with reusable blueprints for complex reasoning patterns like Chain-of-Thought, dynamic few-shot learning with semantic selection, and robust structured output enforcement using JSON and Pydantic. By applying these patterns, developers can reduce non-deterministic behavior, optimize token consumption, and build more resilient AI-powered applications that transition seamlessly from prototype to production.

주요 기능

01Progressive disclosure patterns for iterative prompt refinement

020 GitHub stars

03Dynamic few-shot learning systems with semantic example selection

04Structured JSON and Pydantic schema enforcement for reliable data parsing

05Advanced reasoning elicitation via Chain-of-Thought and self-verification techniques

06Modular system prompt templates for specialized AI personas and role-based behavior

사용 사례

01Developing production-ready AI agents that require high-confidence JSON responses

02Building adaptive RAG systems that utilize dynamic context and example injection

03Optimizing complex logical tasks through multi-step reasoning and verification traces

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sla-te/copilot-converter prompt-engineering-patterns

For use in Claude.ai and ChatGPT

Download Skill