How does domain grounding improve my prompts?

Domain grounding applies established industry theories (like the Pomodoro technique for productivity or Zero Trust for security) to your requirements, ensuring the AI output follows proven professional best practices.

Does this skill help with edge cases?

Yes, Step 2 of the workflow specifically identifies 'Unwanted behavior' patterns, helping you define how the system should handle errors, constraints, and edge cases.

What is the EARS methodology used in this skill?

EARS stands for Easy Approach to Requirements Syntax. it is a methodology used to write clear, unambiguous requirements using five specific patterns: Ubiquitous, Event-driven, State-driven, Conditional, and Unwanted Behavior.

When should I trigger the Prompt Optimizer?

You should use it whenever you find yourself providing loose requirements, or if you receive a request like 'optimize my prompt', 'improve this requirement', or 'make this more specific'.

Prompt Optimizer

Name: Prompt Optimizer
Author: daymade

bydaymade

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147

生産性とワークフロー

Transforms vague requirements into precise, testable specifications using the EARS methodology and domain-specific frameworks.

概要

The Prompt Optimizer is a specialized tool designed to bridge the gap between loose natural language and actionable technical requirements. By utilizing the Easy Approach to Requirements Syntax (EARS) and grounding outputs in established domain theories—such as GTD for productivity or Gestalt for UX—it systematically converts ambiguous feature descriptions into high-fidelity, structured prompts. This skill is essential for developers and product managers who need to ensure AI-generated code is based on clear triggers, measurable criteria, and industry-standard workflows.

主な機能

Automated Example Extraction for generating realistic, testable data scenarios
147 GitHub stars
EARS Syntax Transformation to convert descriptive language into normative specs
Six-step optimization workflow for analyzing and refining original prompts
Domain Theory Grounding using 40+ industry frameworks like BJ Fogg and GTD
Standardized output format including Roles, Skills, Workflows, and Formats

ユースケース

Refining a one-sentence feature request into a comprehensive development roadmap
Generating high-precision prompts for building complex UI/UX components
Converting user stories into testable requirements for automated testing suites

概要

主な機能

Automated Example Extraction for generating realistic, testable data scenarios
147 GitHub stars
EARS Syntax Transformation to convert descriptive language into normative specs
Six-step optimization workflow for analyzing and refining original prompts
Domain Theory Grounding using 40+ industry frameworks like BJ Fogg and GTD
Standardized output format including Roles, Skills, Workflows, and Formats

ユースケース

Refining a one-sentence feature request into a comprehensive development roadmap
Generating high-precision prompts for building complex UI/UX components
Converting user stories into testable requirements for automated testing suites