prompt-creator

Craft structured prompts for Claude, GPT, and other large language models.

3|3|Updated Jan 15, 2026

Search Tags:#Claude #GPT #few-shot #prompt-engineering #system-prompts #prompt-optimization #LLMs

Ready to run

npx skills add https://github.com/twikus/claude-configuration --skill prompt-creator-twikus

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-creator
Source: https://github.com/twikus/claude-configuration/tree/main/claude-code-config/skills/meta-prompt-creator
Command: npx skills add https://github.com/twikus/claude-configuration --skill prompt-creator-twikus

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Creating effective prompts for Claude, GPT, and other large language models is essential to get reliable, relevant outputs. This Skill provides a structured approach to prompt design and optimization, reducing trial-and-error and elevating model performance.

Core Features & Use Cases

Expert prompt engineering for system prompts, user prompts, few-shot examples, and prompt optimization across models.
Applies proven techniques (clarity, structure, reasoning, examples, and advanced patterns) to craft prompts that are clear, specific, and model-aware.
Use Case: Design a system prompt that guides an assistant to provide concise summaries with step-by-step reasoning and consistent formatting.

Quick Start

Draft a high-quality system prompt for a content-writing task: state the goal, specify the target persona, require explicit structure, provide 2-3 few-shot examples, and define success criteria.

Frequently Asked Questions about prompt-creator

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

FAQPage Schema

How do I write effective system prompts for Claude and GPT?▼

Effective system prompts require a clear structure, explicit instructions, repeatable formatting, and few-shot examples. Applied to Claude and GPT, these elements reduce trial-and-error and elevate model performance by ensuring outputs are reliable, relevant, and consistent.

What is few-shot prompt engineering and when should I use it?▼

Few-shot prompt engineering is a technique that provides 2 to 3 demonstration examples within the prompt to guide model behavior. You should use it when you need repeatable formatting and consistent outputs across varied tasks for large language models.

How do I optimize existing prompts for large language models?▼

To optimize existing prompts for large language models, apply proven techniques like clarity, structure, reasoning, and advanced patterns. This structured approach refines instructions and examples to make prompts clear, specific, and model-aware.

Can I use the same prompt structure for both Claude and GPT?▼

Yes, you can apply the same structured approach to both Claude and GPT. Expert prompt engineering ensures prompts are model-aware, utilizing clear structure, explicit instruction, and few-shot examples to optimize performance across different large language models.

What is the best way to structure a prompt for a content-writing assistant?▼

The best way to structure a content-writing prompt is to state the goal, specify the target persona, require explicit structure, provide 2 to 3 few-shot examples, and define success criteria. This ensures concise summaries with step-by-step reasoning and consistent formatting.