Commonly-used-high-value-skills prompt-optimizer
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.
git clone https://github.com/seaworld008/Commonly-used-high-value-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/seaworld008/Commonly-used-high-value-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/task-understanding-decomposition/prompt-optimizer" ~/.claude/skills/seaworld008-commonly-used-high-value-skills-prompt-optimizer-1644ea && rm -rf "$T"
skills/task-understanding-decomposition/prompt-optimizer/SKILL.mdPrompt 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:
- EARS syntax transformation - Convert descriptive language to normative specifications
- Domain theory grounding - Apply relevant industry frameworks (GTD, BJ Fogg, Gestalt, etc.)
- Example extraction - Surface concrete use cases with real data
- 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:
- Ubiquitous:
The system shall <action> - Event-driven:
When <trigger>, the system shall <action> - State-driven:
While <state>, the system shall <action> - Conditional:
If <condition>, the system shall <action> - 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-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:
- 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:
- Identify primary domain from requirement keywords
- Match to 2-4 complementary theories
- Apply theory principles to specific features
- 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:
# 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:
- 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:
## 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:
- Complete EARS syntax rules, all 5 patterns, transformation guidelines, benefitsreferences/ears_syntax.md
- 40+ theories mapped to 10 domains (productivity, UX, gamification, learning, e-commerce, security, etc.)references/domain_theories.md
- Four complete transformation examples (procrastination app, e-commerce product page, learning dashboard, password reset security) with before/after comparisons and reusable templatereferences/examples.md
- Multi-stakeholder requirements, non-functional specs, complex conditional logic patternsreferences/advanced_techniques.md
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