skills.rest
AmidVoshakul
AmidVoshakulCOMMUNITY
Explore all skills by this author →
GitHub

prompt-engineer

Optimize unstructured user input into structured prompts using frameworks like RTF, Chain of Thought, and RODES.

Updated Dec 29, 2025
Search Tags:#automation#productivity#frameworks#optimization#ai#prompting
One-click install
npx skills add https://github.com/AmidVoshakul/chatorai --skill prompt-engineer-amidvoshakul
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-engineer
Source: https://github.com/AmidVoshakul/chatorai/tree/main/assets/skills/prompt-engineer
Command: npx skills add https://github.com/AmidVoshakul/chatorai --skill prompt-engineer-amidvoshakul

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates the guesswork in AI prompting by automatically structuring your vague requests into high-quality, optimized prompts that yield superior results from any language model.

Core Features & Use Cases

  • Framework Intelligence: Automatically selects and blends 11 proven prompting frameworks like Chain of Thought, RTF, and RODES based on your specific task.
  • Magic Mode: Operates silently to provide polished, ready-to-use prompts without requiring you to learn complex prompting jargon.
  • Use Case: If you need to design a complex system architecture, simply describe your goal, and the skill will generate a structured prompt including roles, objectives, step-by-step reasoning, and validation criteria.

Quick Start

Invoke the skill by typing improve this prompt followed by your rough idea to receive an optimized version instantly.

Frequently Asked Questions about prompt-engineer

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

FAQPage Schema
How do I optimize AI prompts for better results?▼

Optimize AI prompts by structuring unstructured input into high-performance prompts using established frameworks like RTF, Chain of Thought, and RODES, ensuring output is self-contained, measurable, and model-agnostic.

What is the best way to structure a prompt for complex coding tasks?▼

The best way to structure prompts for coding tasks is to apply framework intelligence, which automatically maps your goal to roles, objectives, step-by-step reasoning, and validation criteria for precise results.

How do prompting frameworks like Chain of Thought and RODES improve AI outputs?▼

Prompting frameworks like Chain of Thought and RODES improve AI outputs by applying intelligent intent analysis and structured reasoning, eliminating guesswork and making the generated prompts self-contained and measurable.

Can I use automated prompt generation for strategic communication and goal-setting?▼

Yes, you can use automated prompt generation for strategic communication and goal-setting, as the framework intelligence handles diverse tasks including technical design and coding across any terminal context.

Do I need to learn prompting jargon to generate expert-level prompts?▼

No, you do not need to learn prompting jargon because Magic Mode operates silently to provide polished, ready-to-use prompts directly from your rough ideas without requiring technical framework knowledge.

Related Skills

Explore More Content & Communication Skills→
baselakkad585-makerbaselakkad585-maker

prompt-engineer

Transform unstructured prompts into optimized prompts using prompting frameworks.

Community
Advanced
89jobrien89jobrien
4

prompt-optimization

Optimize LLM prompts with structured design, few-shot patterns, and chain-of-thought reasoning.

Community
Advanced
KrishpotanwarKrishpotanwar

stream-chain

Coordinate multi-agent sequences for data processing and code analysis.

Community
Advanced
flosrnflosrn

create-prompt

Create prompts for LLMs using XML, markdown, and few-shot examples.

Community
Intermediate