/prompt-enhance

name: prompt-enhance
description: >
  Enhance and improve existing AI prompts using professional techniques
  from a 2,500+ prompt database. Adds detail, fixes structure, optimizes
  for specific models, and applies proven patterns from top-performing prompts.
  Use when user says "enhance my prompt", "improve this prompt",
  "make this prompt better", "optimize prompt", "fix my prompt",
  or "upgrade this prompt".

Prompt Enhancer

Take any existing prompt and supercharge it using techniques from 2,500+ curated prompts.

Enhancement Workflow

Step 1: Analyze the Input Prompt

Evaluate the user's prompt on these dimensions:

• **Specificity** (1-5): How detailed is the subject description?
• **Technical quality** (1-5): Camera, lighting, composition details?
• **Style clarity** (1-5): Is the aesthetic clearly defined?
• **Model optimization** (1-5): Uses model-specific syntax correctly?
• **Length appropriateness** (1-5): Right length for the target model?

Present a brief score card before enhancing.

Step 2: Find Similar Top Prompts

Search for high-quality reference prompts:

python3 {PROMPT_ENGINE_DIR}/scripts/search_prompts.py "KEY_TERMS" --limit 5

Step 3: Apply Enhancement Techniques

Choose from these enhancement strategies based on what's missing:

**Detail Injection** (for low specificity):

• Add material textures ("brushed aluminum", "weathered leather")
• Add environmental details ("dust particles in light", "morning dew")
• Add character details ("freckled skin", "calloused hands")

**Technical Elevation** (for missing camera/lighting):

• Add camera specs ("shot on Canon R5, 85mm f/1.2")
• Add lighting ("golden hour backlighting", "Rembrandt lighting")
• Add film stocks ("Kodak Portra 400 colors", "Fuji Velvia saturation")

**Style Anchoring** (for unclear aesthetic):

• Add photographer/artist references ("in the style of Annie Leibovitz")
• Add film/era references ("Y2K aesthetic", "1970s Kodachrome")
• Add mood keywords ("moody", "ethereal", "gritty")

**Negative Refinement** (for models that support it):

• Add negative prompts to exclude unwanted elements
• Specify what NOT to include ("no text", "no watermark")

**Structure Optimization** (for poor organization):

• Reorder elements: subject first, then environment, then style
• Group related modifiers together
• Remove redundant or conflicting terms

Step 4: Present Enhanced Version

Output format: 1. **Original prompt** (for comparison) 2. **Enhanced prompt** (the improved version) 3. **What changed** (bullet list of specific improvements) 4. **Score improvement** (before -> after on 5-point scale) 5. **Variations** (2-3 alternative enhanced versions)

Enhancement Rules

• Never remove the user's core intent/subject
• Preserve the user's preferred style if stated
• Keep enhancements relevant to the target model
• Don't over-engineer: some prompts are intentionally minimal
• Always explain WHY each change was made