prompt-crafting

Refine vague prompts into precise, model-specific prompts with explicit goals and output structure.

1|Updated Jan 5, 2023

Search Tags:#refinement #claude #gemini #gpt #prompt-engineering #ai-models #prompt

Ready to run

npx skills add https://github.com/riez/dots --skill prompt-crafting

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-crafting
Source: https://github.com/riez/dots/tree/main/.config/agentic/skills/prompt-crafting
Command: npx skills add https://github.com/riez/dots --skill prompt-crafting

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Refine vague prompts into precise, model-specific prompts. This guide helps convert underspecified requests into clear, outcome-oriented instructions that align with the target model family.

Core Features & Use Cases

Guidance on creating concrete prompts with explicit goals, context, constraints, acceptance criteria, and output shape.
Model-specific refinement tips for GPT, Claude, and Gemini to ensure consistent results across families.
Real-world scenarios where prompt crafting improves quality and reduces misinterpretation.

Quick Start

Refine a rough prompt into a model-specific prompt with explicit sections and a clear output format.

Frequently Asked Questions about prompt-crafting

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

FAQPage Schema

How do I refine a vague prompt into a precise, model-specific prompt?▼

To refine a vague prompt, you convert underspecified requests into clear instructions by defining explicit goals, context, constraints, acceptance criteria, and a structured output format tailored to the target model family.

What is the best way to structure prompts for different AI models like GPT, Claude, and Gemini?▼

Structuring prompts for GPT, Claude, and Gemini requires applying model-specific refinement tips to ensure consistent results across families, focusing on explicit goals and a clearly defined output shape for each model.

When do I need prompt engineering for complex tasks?▼

You need prompt engineering for complex tasks when initial requests are underspecified, aiming to reduce misinterpretation and improve output quality by enforcing explicit context, constraints, and success criteria in the instructions.

How can I add explicit constraints and success criteria to an underspecified AI prompt?▼

You add explicit constraints and success criteria by transforming an underspecified request into an outcome-oriented instruction, defining the exact boundaries, goals, and acceptance metrics required for the task to succeed.

Does prompt crafting work for improving output consistency across different AI model families?▼

Prompt crafting works for improving output consistency by applying model-specific refinement tips, ensuring that instructions align with the target families of GPT, Claude, and Gemini to reduce misinterpretation.

Why does my AI model misinterpret complex tasks, and how can I fix it?▼

AI models misinterpret complex tasks due to underspecified requests; fixing this requires converting vague inputs into precise prompts that enforce explicit goals, context, constraints, and a defined output structure.