Add new prompt-optimizer skill (v1.1.0) for transforming vague prompts into precise EARS specifications: New Features: - EARS (Easy Approach to Requirements Syntax) transformation with 5 patterns - 6-step optimization workflow (analyze, transform, theories, examples, enhance, present) - Domain theory grounding (40+ frameworks across 10 domains) - Role/Skills/Workflows/Examples/Formats prompt enhancement framework - Progressive disclosure with 4 bundled reference files Skill Improvements (v1.0.0 → v1.1.0): - Reduced SKILL.md from 369 to 195 lines (47% reduction) - Added advanced_techniques.md (325 lines) for complex scenarios - Added 4th complete example (password reset security) - Added attribution to 阿星AI工作室 (A-Xing AI Studio) - Enhanced reference loading guidance Marketplace Updates: - Updated marketplace to v1.11.0 (17 → 18 skills) - Updated all documentation (README.md, README.zh-CN.md, CLAUDE.md) - Added Chinese and English descriptions with attribution 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
196 lines
7.8 KiB
Markdown
196 lines
7.8 KiB
Markdown
---
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name: prompt-optimizer
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description: 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.
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---
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# Prompt Optimizer
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## Overview
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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.
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**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)](https://mp.weixin.qq.com/s/yUVX-9FovSq7ZGChkHpuXQ), which demonstrated practical EARS application for prompt enhancement.
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**Four-layer enhancement process:**
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1. **EARS syntax transformation** - Convert descriptive language to normative specifications
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2. **Domain theory grounding** - Apply relevant industry frameworks (GTD, BJ Fogg, Gestalt, etc.)
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3. **Example extraction** - Surface concrete use cases with real data
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4. **Structured prompt generation** - Format using Role/Skills/Workflows/Examples/Formats framework
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## When to Use
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Apply when:
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- User provides vague feature requests ("build a dashboard", "create a reminder app")
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- Requirements lack specific conditions, triggers, or measurable outcomes
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- Natural language descriptions need conversion to testable specifications
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- User explicitly requests prompt optimization or requirement refinement
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## Six-Step Optimization Workflow
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### Step 1: Analyze Original Requirement
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Identify weaknesses:
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- **Overly broad** - "Add user authentication" → Missing password requirements, session management
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- **Missing triggers** - "Send notifications" → Missing when/why notifications trigger
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- **Ambiguous actions** - "Make it user-friendly" → No measurable usability criteria
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- **No constraints** - "Process payments" → Missing security, compliance requirements
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### Step 2: Apply EARS Transformation
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Convert requirements to EARS patterns. See `references/ears_syntax.md` for complete syntax rules.
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**Five core patterns:**
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1. **Ubiquitous**: `The system shall <action>`
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2. **Event-driven**: `When <trigger>, the system shall <action>`
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3. **State-driven**: `While <state>, the system shall <action>`
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4. **Conditional**: `If <condition>, the system shall <action>`
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5. **Unwanted behavior**: `If <condition>, the system shall prevent <unwanted action>`
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**Quick example:**
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```
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Before: "Create a reminder app with task management"
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After (EARS):
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1. When user creates a task, the system shall guide decomposition into executable sub-tasks
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2. When task deadline is within 30 minutes AND user has not started, the system shall send notification with sound alert
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3. When user completes a sub-task, the system shall update progress and provide positive feedback
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```
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**Transformation checklist:**
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- [ ] Identify implicit conditions and make explicit
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- [ ] Specify triggering events or states
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- [ ] Use precise action verbs (shall, must, should)
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- [ ] Add measurable criteria ("within 30 minutes", "at least 8 characters")
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- [ ] Break compound requirements into atomic statements
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- [ ] Remove ambiguous language ("user-friendly", "fast")
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### Step 3: Identify Domain Theories
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Match requirements to established frameworks. See `references/domain_theories.md` for full catalog.
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**Common domain mappings:**
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- **Productivity** → GTD, Pomodoro, Eisenhower Matrix
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- **Behavior Change** → BJ Fogg Model (B=MAT), Atomic Habits
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- **UX Design** → Hick's Law, Fitts's Law, Gestalt Principles
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- **Security** → Zero Trust, Defense in Depth, Privacy by Design
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**Selection process:**
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1. Identify primary domain from requirement keywords
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2. Match to 2-4 complementary theories
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3. Apply theory principles to specific features
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4. Cite theories in enhanced prompt for credibility
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### Step 4: Extract Concrete Examples
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Generate specific examples with real data:
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- User scenarios: "When user logs in on mobile device..."
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- Data examples: "Product: 'Laptop', Price: $999, Stock: 15"
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- Workflow examples: "Task: Write report → Sub-tasks: Research (2h), Draft (3h), Edit (1h)"
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Examples must be **realistic**, **specific**, **varied** (success/error/edge cases), and **testable**.
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### Step 5: Generate Enhanced Prompt
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Structure using the standard framework:
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```markdown
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# Role
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[Specific expert role with domain expertise]
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## Skills
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- [Core capability 1]
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- [Core capability 2]
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[List 5-8 skills aligned with domain theories]
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## Workflows
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1. [Phase 1] - [Key activities]
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2. [Phase 2] - [Key activities]
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[Complete step-by-step process]
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## Examples
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[Concrete examples with real data, not placeholders]
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## Formats
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[Precise output specifications:
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- File types, structure requirements
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- Design/styling expectations
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- Technical constraints
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- Deliverable checklist]
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```
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**Quality criteria:**
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- **Role specificity**: "Product designer specializing in time management apps" > "Designer"
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- **Theory grounding**: Reference frameworks explicitly
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- **Actionable workflows**: Clear inputs/outputs and decision points
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- **Concrete examples**: Real data, not "Example 1", "Example 2"
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- **Measurable formats**: Specific requirements, not "good design"
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### Step 6: Present Optimization Results
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Output in structured format:
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```markdown
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## Original Requirement
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[User's vague requirement]
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**Identified Issues:**
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- [Issue 1: e.g., "Lacks specific trigger conditions"]
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- [Issue 2: e.g., "No measurable success criteria"]
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## EARS Transformation
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[Numbered list of EARS-formatted requirements]
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## Domain & Theories
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**Primary Domain:** [e.g., Authentication Security]
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**Applicable Theories:**
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- **[Theory 1]** - [Brief relevance]
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- **[Theory 2]** - [Brief relevance]
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## Enhanced Prompt
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[Complete Role/Skills/Workflows/Examples/Formats prompt]
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---
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**How to use:**
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[Brief guidance on applying the prompt]
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```
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## Advanced Techniques
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For complex scenarios, see `references/advanced_techniques.md`:
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- **Multi-stakeholder requirements** - EARS statements for each user type
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- **Non-functional requirements** - Performance, security, scalability with quantified thresholds
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- **Complex conditional logic** - Nested conditions with boolean operators
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## Quick Reference
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**Do's:**
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✅ Break down compound requirements (one EARS statement per requirement)
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✅ Specify measurable criteria (numbers, timeframes, percentages)
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✅ Include error/edge cases
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✅ Ground in established theories
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✅ Use concrete examples with real data
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**Don'ts:**
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❌ Avoid vague language ("fast", "user-friendly")
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❌ Don't assume implicit knowledge
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❌ Don't mix multiple actions in one statement
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❌ Don't use placeholders in examples
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## Resources
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Load these reference files as needed:
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- **`references/ears_syntax.md`** - Complete EARS syntax rules, all 5 patterns, transformation guidelines, benefits
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- **`references/domain_theories.md`** - 40+ theories mapped to 10 domains (productivity, UX, gamification, learning, e-commerce, security, etc.)
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- **`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
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- **`references/advanced_techniques.md`** - Multi-stakeholder requirements, non-functional specs, complex conditional logic patterns
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**When to load references:**
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- EARS syntax clarification needed → `ears_syntax.md`
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- Domain theory selection requires extensive options → `domain_theories.md`
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- User requests multiple optimization examples → `examples.md`
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- Complex requirements with multiple stakeholders or non-functional specs → `advanced_techniques.md`
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