prompt-optimizer/SKILL.md
Transform vague prompts into precise, well-structured specifications using EARS (Easy Approach to Requirements Syntax) methodology. This skill should be used when users provide loose requirements, ambiguous feature descriptions, or need to enhance prompts for AI-generated code, products, or documents. Triggers include requests to "optimize my prompt", "improve this requirement", "make this more specific", or when raw requirements lack detail and structure.
npx skillsauth add fernandezbaptiste/claude-code-skills prompt-optimizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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:
Apply when:
Identify weaknesses:
Convert requirements to EARS patterns. See references/ears_syntax.md for complete syntax rules.
Five core patterns:
The system shall <action>When <trigger>, the system shall <action>While <state>, the system shall <action>If <condition>, the system shall <action>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-tasks
2. When task deadline is within 30 minutes AND user has not started, the system shall send notification with sound alert
3. When user completes a sub-task, the system shall update progress and provide positive feedback
Transformation checklist:
Match requirements to established frameworks. See references/domain_theories.md for full catalog.
Common domain mappings:
Selection process:
Generate specific examples with real data:
Examples must be realistic, specific, varied (success/error/edge cases), and testable.
Structure using the standard framework:
# Role
[Specific expert role with domain expertise]
## Skills
- [Core capability 1]
- [Core capability 2]
[List 5-8 skills aligned with domain theories]
## Workflows
1. [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:
Output in structured format:
## 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]
For complex scenarios, see references/advanced_techniques.md:
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
Load these reference files as needed:
references/ears_syntax.md - Complete EARS syntax rules, all 5 patterns, transformation guidelines, benefitsreferences/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 templatereferences/advanced_techniques.md - Multi-stakeholder requirements, non-functional specs, complex conditional logic patternsWhen to load references:
ears_syntax.mddomain_theories.mdexamples.mdadvanced_techniques.mddata-ai
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