prompt-optimizer

Convert vague prompts into testable EARS-based specifications.

Updated Aug 23, 2026

Search Tags:#specification #requirements #ears #prompt #prompt-optimization #domain-theory

Ready to run

npx skills add https://github.com/aleister1102/skills --skill prompt-optimizer-aleister1102

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-optimizer
Source: https://github.com/aleister1102/skills/tree/main/prompt-optimizer
Command: npx skills add https://github.com/aleister1102/skills --skill prompt-optimizer-aleister1102

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts vague prompts into precise, testable EARS-based specifications to create clearer, verifiable requirements and prompts.

Core Features & Use Cases

EARS transformation: converts descriptive requirements into EARS-formatted statements.
Domain-theory grounding: maps requirements to established theories to improve credibility and rigor.
Structured prompt generation: outputs Role/Skills/Workflows/Examples/Formats ready for implementation.
Quick-start guidance: provides actionable steps to start refining prompts.

Quick Start

Provide a vague prompt, and I will generate a complete EARS-based specification with domain grounding and a structured prompt ready for implementation.

Frequently Asked Questions about prompt-optimizer

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

FAQPage Schema

How do I convert vague prompts into testable specifications?▼

EARS transformation works by converting descriptive requirements into precise EARS-formatted statements that are verifiable. It grounds requirements in established domain theories to improve credibility and rigor, outputting a structured Role/Skills/Workflows/Examples/Formats prompt for implementation.

How do I refine a prompt for development workflows?▼

To refine a prompt for development workflows, you provide the vague prompt to generate a complete EARS-based specification. This end-to-end specification includes domain grounding, examples, and a structured prompt format ready for immediate implementation in design, development, and evaluation tasks.

What is EARS transformation for prompt optimization?▼

EARS transformation for prompt optimization is a method that converts descriptive requirements into precise, testable EARS-formatted statements. It maps requirements to established domain theories to improve credibility, delivering verifiable specifications and structured prompts for implementation.

When do I need EARS-based specifications for prompt refinement?▼

You need EARS-based specifications when vague prompts require conversion into clearer, verifiable requirements. This approach applies across design, development, and evaluation workflows to ensure your prompts are precise, testable, and grounded in established domain theories.

Can I use domain-theory grounding to improve requirement credibility?▼

Yes, you can use domain-theory grounding to improve requirement credibility by mapping your specifications to established theories. This technique enhances rigor during EARS transformation, ensuring the generated structured prompts are verifiable and grounded in recognized domain frameworks.

What is the best way to structure prompts for implementation?▼

The best way to structure prompts for implementation is to generate a Role/Skills/Workflows/Examples/Formats output. This structured format is produced after completing EARS transformation and domain-theory grounding, delivering a complete specification ready for development workflows.