prompt-engineering-patterns

Define PromptTemplate objects and render them with FewShotSelector.

Updated Aug 23, 2026

Search Tags:#templates #chain-of-thought #LLM #few-shot #prompt-engineering #system-prompts #prompt-optimization

One-click install

npx skills add https://github.com/atalovesyou/claude-skills-pack --skill prompt-engineering-patterns-atalovesyou

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: prompt-engineering-patterns
Source: https://github.com/atalovesyou/claude-skills-pack/tree/main/skills/prompt-engineering-patterns
Command: npx skills add https://github.com/atalovesyou/claude-skills-pack --skill prompt-engineering-patterns-atalovesyou

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Master production-grade prompt engineering to maximize LLM performance, reliability, and controllability.

Core Features & Use Cases

Few-Shot Learning, Chain-of-Thought prompting, Template Systems
System prompts, verification steps, and prompt templates

Quick Start

Define a PromptTemplate and render with a FewShotSelector; demonstrate with a simple example.