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prompt-adapt

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".

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gabrielmoreira/agent-skills-mirror
Works withOpenAI

Run score Not tested

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SKILL.md (original)

Review the instructions the agent will receive before you install.

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)

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