prompt-optimizer

安装量: 36
排名: #19350

安装

npx skills add https://github.com/daymade/claude-code-skills --skill prompt-optimizer

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: 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 Event-driven : When , the system shall State-driven : While , the system shall Conditional : If , the system shall Unwanted behavior : If , the system shall prevent 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: 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

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