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prompt-engineering

Designs system prompts, few-shot templates, and testing workflows for Claude, GPT, and open-source models.

Updated Mar 27, 2026
Search Tags:#templates#chain-of-thought#ai#few-shot#prompt-engineering#prompt#system-prompt
One-click install
npx skills add https://github.com/goodstoriesworld/coco-agent-skills --skill prompt-engineering-goodstoriesworld
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-engineering
Source: https://github.com/goodstoriesworld/coco-agent-skills/tree/main/vendored/prompt-engineering
Command: npx skills add https://github.com/goodstoriesworld/coco-agent-skills --skill prompt-engineering-goodstoriesworld

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prompt engineering helps teams design effective prompts to reliably steer AI behavior, reducing errors and increasing consistency across tasks.

Core Features & Use Cases

  • System prompt design and chain-of-thought scaffolding to improve reasoning reliability.
  • Structured prompt templates, few-shot examples, and output formats to standardize results.
  • Use cases include building multi-step workflows, optimizing model accuracy, and creating reusable prompt libraries for different models.

Quick Start

Provide a clear system prompt, a concrete task, and a few example prompts to calibrate the model and iterate effectively.

Frequently Asked Questions about prompt-engineering

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

FAQPage Schema
How do I design system prompts to get reliable AI outputs?▼

System prompts steer model behavior by providing explicit guidance, structured output formats, and chain-of-thought scaffolding to increase reasoning reliability and standardize results.

What is few-shot prompting and how do I use it with structured templates?▼

Few-shot prompting uses concrete example prompts within structured templates to calibrate the model, standardize outputs, and improve accuracy across Claude, GPT, and open-source models.

Can I build multi-step prompt chains for different AI models?▼

You can build multi-step workflows and reusable prompt libraries by applying pattern-based prompts and iterative evaluation across Claude, GPT, and open-source models.

Why does my AI model produce inconsistent results from the same prompt?▼

Inconsistent results often occur when prompts lack structured output formats and few-shot examples; applying best-practice templates and iterative testing workflows standardizes results.

Does chain-of-thought scaffolding improve reasoning reliability for AI tasks?▼

Chain-of-thought scaffolding improves reasoning reliability by breaking down tasks into structured steps within system prompts, guiding models through explicit reasoning patterns.

What's the best way to create a reusable prompt library for AI workflows?▼

Create reusable prompt libraries by standardizing system prompts, few-shot templates, and structured output formats, enabling consistent model behavior across different workflows.

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