Prompt Optimizer

by daymade2c6d263d1fccNo license1.4K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

Transforms vague prompts or feature requests into precise, testable specifications using EARS (Easy Approach to Requirements Syntax) grounded in relevant domain theories (GTD, BJ Fogg, Gestalt). Use when requirements lack triggers or measurable outcomes, or the user asks to "optimize my prompt" / "improve this requirement" / "make this more specific".

Instructions onlyAI & Agents
AI-generated overview

Rewrites vague prompts and feature requests into precise, testable EARS specifications grounded in domain theories.

What it does
Turns loose natural-language requirements into structured, testable specifications using EARS patterns such as event-driven, state-driven and conditional statements. It also maps requirements to relevant domain frameworks, extracts concrete examples with realistic data, and produces an enhanced prompt in a Role/Skills/Workflows/Examples/Formats structure. Output includes the original requirement, identified issues, the EARS transformation, applicable theories and the enhanced prompt.
When to use it
Use when a request is vague, lacks triggers or measurable outcomes, or needs conversion into testable requirements. It also fits explicit requests to optimize a prompt or improve a requirement.
Requirements
No scripts; instructions and four reference markdown files only. No packages, credentials or network access are required.

Prompt Optimizer

Overview

Optimize vague prompts into precise, actionable specifications using EARS (Easy Approach to Requirements Syntax) - a Rolls-Royce methodology for transforming natural language into structured, testable requirements.

Methodology inspired by: This skill's approach to combining EARS with domain theory grounding was inspired by 阿星AI工作室 (A-Xing AI Studio), which demonstrated practical EARS application for prompt enhancement.

Four-layer enhancement process:

  1. EARS syntax transformation - Convert descriptive language to normative specifications
  2. Domain theory grounding - Apply relevant industry frameworks (GTD, BJ Fogg, Gestalt, etc.)
  3. Example extraction - Surface concrete use cases with real data
  4. Structured prompt generation - Format using Role/Skills/Workflows/Examples/Formats framework

When to Use

Apply when:

  • User provides vague feature requests ("build a dashboard", "create a reminder app")
  • Requirements lack specific conditions, triggers, or measurable outcomes
  • Natural language descriptions need conversion to testable specifications
  • User explicitly requests prompt optimization or requirement refinement

Six-Step Optimization Workflow

Step 1: Analyze Original Requirement

Identify weaknesses:

  • Overly broad - "Add user authentication" → Missing password requirements, session management
  • Missing triggers - "Send notifications" → Missing when/why notifications trigger
  • Ambiguous actions - "Make it user-friendly" → No measurable usability criteria
  • No constraints - "Process payments" → Missing security, compliance requirements

Step 2: Apply EARS Transformation

Convert requirements to EARS patterns. See references/ears_syntax.md for complete syntax rules.

Five core patterns:

  1. Ubiquitous: The system shall <action>
  2. Event-driven: When <trigger>, the system shall <action>
  3. State-driven: While <state>, the system shall <action>
  4. Conditional: If <condition>, the system shall <action>
  5. Unwanted behavior: If <condition>, the system shall prevent <unwanted action>

Quick example:

Before: "Create a reminder app with task management"
After (EARS):1. When user creates a task, the system shall guide decomposition into executable sub-tasks2. When task deadline is within 30 minutes AND user has not started, the system shall send notification with sound alert3. When user completes a sub-task, the system shall update progress and provide positive feedback

Transformation checklist:

  • Identify implicit conditions and make explicit
  • Specify triggering events or states
  • Use precise action verbs (shall, must, should)
  • Add measurable criteria ("within 30 minutes", "at least 8 characters")
  • Break compound requirements into atomic statements
  • Remove ambiguous language ("user-friendly", "fast")

Step 3: Identify Domain Theories

Match requirements to established frameworks. See references/domain_theories.md for full catalog.

Common domain mappings:

  • Productivity → GTD, Pomodoro, Eisenhower Matrix
  • Behavior Change → BJ Fogg Model (B=MAT), Atomic Habits
  • UX Design → Hick's Law, Fitts's Law, Gestalt Principles
  • Security → Zero Trust, Defense in Depth, Privacy by Design

Selection process:

  1. Identify primary domain from requirement keywords
  2. Match to 2-4 complementary theories
  3. Apply theory principles to specific features
  4. Cite theories in enhanced prompt for credibility

Step 4: Extract Concrete Examples

Generate specific examples with real data:

  • User scenarios: "When user logs in on mobile device..."
  • Data examples: "Product: 'Laptop', Price: $999, Stock: 15"
  • Workflow examples: "Task: Write report → Sub-tasks: Research (2h), Draft (3h), Edit (1h)"

Examples must be realistic, specific, varied (success/error/edge cases), and testable.

Step 5: Generate Enhanced Prompt

Structure using the standard framework:

markdown
# Role[Specific expert role with domain expertise]
## Skills- [Core capability 1]- [Core capability 2][List 5-8 skills aligned with domain theories]
## Workflows1. [Phase 1] - [Key activities]2. [Phase 2] - [Key activities][Complete step-by-step process]
## Examples[Concrete examples with real data, not placeholders]
## Formats[Precise output specifications:- File types, structure requirements- Design/styling expectations- Technical constraints- Deliverable checklist]

Quality criteria:

  • Role specificity: "Product designer specializing in time management apps" > "Designer"
  • Theory grounding: Reference frameworks explicitly
  • Actionable workflows: Clear inputs/outputs and decision points
  • Concrete examples: Real data, not "Example 1", "Example 2"
  • Measurable formats: Specific requirements, not "good design"

Step 6: Present Optimization Results

Output in structured format:

markdown
## Original Requirement[User's vague requirement]
**Identified Issues:**- [Issue 1: e.g., "Lacks specific trigger conditions"]- [Issue 2: e.g., "No measurable success criteria"]
## EARS Transformation[Numbered list of EARS-formatted requirements]
## Domain & Theories**Primary Domain:** [e.g., Authentication Security]
**Applicable Theories:**- **[Theory 1]** - [Brief relevance]- **[Theory 2]** - [Brief relevance]
## Enhanced Prompt[Complete Role/Skills/Workflows/Examples/Formats prompt]
---
**How to use:**[Brief guidance on applying the prompt]

Advanced Techniques

For complex scenarios, see references/advanced_techniques.md:

  • Multi-stakeholder requirements - EARS statements for each user type
  • Non-functional requirements - Performance, security, scalability with quantified thresholds
  • Complex conditional logic - Nested conditions with boolean operators

Quick Reference

Do's: ✅ Break down compound requirements (one EARS statement per requirement) ✅ Specify measurable criteria (numbers, timeframes, percentages) ✅ Include error/edge cases ✅ Ground in established theories ✅ Use concrete examples with real data

Don'ts: ❌ Avoid vague language ("fast", "user-friendly") ❌ Don't assume implicit knowledge ❌ Don't mix multiple actions in one statement ❌ Don't use placeholders in examples

Resources

Load these reference files as needed:

  • references/ears_syntax.md - Complete EARS syntax rules, all 5 patterns, transformation guidelines, benefits
  • references/domain_theories.md - 40+ theories mapped to 10 domains (productivity, UX, gamification, learning, e-commerce, security, etc.)
  • references/examples.md - Four complete transformation examples (procrastination app, e-commerce product page, learning dashboard, password reset security) with before/after comparisons and reusable template
  • references/advanced_techniques.md - Multi-stakeholder requirements, non-functional specs, complex conditional logic patterns

When to load references:

  • EARS syntax clarification needed → ears_syntax.md
  • Domain theory selection requires extensive options → domain_theories.md
  • User requests multiple optimization examples → examples.md
  • Complex requirements with multiple stakeholders or non-functional specs → advanced_techniques.md

Source and attribution

Source:daymade/claude-code-skillsinprompt-optimizerat commit2c6d263

License: No license

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