/prompt-adapt

name: prompt-adapt
description: >
  Adapt and convert AI prompts between different models and platforms.
  Translates between Midjourney, Flux, Leonardo AI, DALL-E, Sora, Imagen,
  Stable Diffusion, Adobe Firefly, Ideogram, and more. Handles syntax
  differences, parameter mapping, and model-specific optimizations.
  Use when user says "adapt prompt", "convert prompt", "translate prompt",
  "port to flux", "midjourney to dall-e", or "change model".

Prompt Adapter

Convert prompts between AI models while preserving intent and maximizing output quality.

Adaptation Workflow

Step 1: Identify Source and Target

Determine: 1. **Source model**: What model was this prompt written for? 2. **Target model**: What model should it run on? 3. **Priority**: Preserve style fidelity or optimize for target strengths?

Step 2: Analyze Source Prompt

Break down the prompt into components:

• Core subject/action
• Style modifiers
• Technical parameters (model-specific)
• Negative prompts (if any)
• Aspect ratio / dimensions

Step 3: Apply Model Translation Rules

Load `{PROMPT_ENGINE_DIR}/references/model-guide.md` for detailed rules. Key translations:

**Midjourney -> Flux:**

• Remove `--ar`, `--v`, `--style`, `--s`, `--chaos` parameters
• Expand shorthand into natural language descriptions
• Flux prefers longer, more descriptive prompts
• Remove `::` weight syntax, integrate naturally

**Midjourney -> DALL-E:**

• Remove all `--` parameters
• Rewrite as clear, direct descriptions
• DALL-E prefers straightforward language over artistic jargon
• Remove negative prompts (DALL-E doesn't support them well)

**Flux -> Midjourney:**

• Add `--ar` for aspect ratio
• Add `--v 6.1` or appropriate version
• Condense long descriptions into key phrases
• Add style parameters (`--style raw` for photorealistic)

**Any -> Sora (Video):**

• Add camera movement descriptions (pan, zoom, tracking, etc.)
• Add temporal flow ("the scene transitions from... to...")
• Specify duration if possible
• Focus on motion and action over static details

**Any -> Leonardo AI:**

• Reference specific Leonardo models (Phoenix, Alchemy, etc.)
• Use Leonardo-specific quality tokens
• Adapt negative prompts to Leonardo format

Step 4: Search for Target Model Examples

Find reference prompts in the target model:

python3 {PROMPT_ENGINE_DIR}/scripts/search_prompts.py "SUBJECT" --model TARGET_MODEL --limit 3

Use these as style references for the adaptation.

Step 5: Present Adaptation

Output format: 1. **Original prompt** (source model labeled) 2. **Adapted prompt** (target model labeled) 3. **Translation notes** (what changed and why) 4. **Parameter mapping** (source params -> target params) 5. **Confidence level** (High/Medium/Low -- based on model compatibility)

Common Pitfalls

• Midjourney weight syntax (`::2`) has no direct equivalent in most models
• DALL-E ignores most style parameters -- weave them into descriptions
• Sora needs temporal language that image models don't use
• Aspect ratios must be specified differently per platform
• Some styles only work well on specific models (e.g., `--niji` is Midjourney-only)