prompt-enhance

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