prompt-engineering

Formalize prompt techniques for structured, reliable AI responses.

Updated Feb 9, 2026

Search Tags:#react #chain-of-thought #few-shot #prompt-engineering #structured-output #prompt #role-play

Ready to run

npx skills add https://github.com/Xza85hrf/claude-code-agent-kit --skill prompt-engineering-xza85hrf

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-engineering
Source: https://github.com/Xza85hrf/claude-code-agent-kit/tree/main/.claude/skills/meta/prompt-engineering
Command: npx skills add https://github.com/Xza85hrf/claude-code-agent-kit --skill prompt-engineering-xza85hrf

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps AI teams design prompts that minimize hallucinations, enforce structured outputs, and enable role-based behavior across tasks.

Core Features & Use Cases

Techniques selection and guidance for Zero-shot, Few-shot, Chain-of-thought, Self-consistency, Tree-of-thought, ReAct, and Role-play to improve reliability.
Structured output patterns and guidance on when to use JSON, XML, or Markdown formats, with schemas and validation tips.
Use cases include prompt design for code assistants, data analysis pipelines, content generation, and safety-aware decision support.

Quick Start

Design a prompt that combines role-play with a few-shot example to force the model to output structured JSON.

Frequently Asked Questions about prompt-engineering

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I write prompts that enforce structured JSON output from an LLM?▼

To enforce structured JSON output, apply structured output patterns with defined schemas and validation tips, combining them with role-play and few-shot examples to constrain the model's response format reliably.

What is the best way to reduce AI hallucinations in data extraction pipelines?▼

The best way to reduce AI hallucinations in data extraction pipelines is to formalize prompt behavior using techniques like few-shot examples, chain-of-thought, and self-consistency for repeatable and reliable responses.

When should I use chain-of-thought versus few-shot prompting for code generation?▼

Use few-shot prompting to demonstrate expected code formats or patterns, and apply chain-of-thought when the code generation task requires complex multi-step reasoning before producing the final output.

Can I implement role-play and ReAct techniques for AI assistants without external dependencies?▼

Yes, you can implement role-play and ReAct techniques without external dependencies by structuring your prompts to define specific roles and reasoning-action loops directly within the model instructions.

How do I design prompts for safety-aware decision support systems?▼

Design prompts for safety-aware decision support by specifying safety considerations directly within the prompt structure and using self-consistency or tree-of-thought techniques to validate reasoning paths before outputting decisions.