image-remix

name

image-remix

description

Invoke when a user shares a reference image and wants new images with the same "feel" — composition, color palette, lighting, style, or mood — but different content. Analyzes the image across 10 aesthetic dimensions, collapses into 3 axes (Form / Aesthetic / Mood), then generates using a model matched to the original's origin with adapted prompt style. Supports iterative refinement. Trigger on: "remix this image," "make something like this," "same vibe different content," "I like this style make me…," "replicate this feel," "same style different content," "make one with this feeling," "create something in this style," "I like how this image feels," "recreate this effect," "style transfer," "image remix," or any request where someone shares an image and wants new images inspired by its aesthetic. Key distinction: user wants images INSPIRED BY the reference, not a copy or edit of it. Do NOT trigger for: image editing, upscaling, format conversion, image-to-video generation.

Image Remix — Image Inspiration Remix Assistant

The user sends a reference image; analyze what makes it "good," then generate images that retain the core feel but with entirely new content.

Core Philosophy

• Origin-Driven Generation: First determine which model/camera/hand-drawn the original came from, then directly call the corresponding model + matching prompt style — MJ uses keyword stacking, Flux uses natural language long sentences. Origin, tool, and writing style are unified as one
• 10D -> 3D Collapse: Internal 10-dimension analysis, collapsed into 3 user-visible dimensions: Form / Aesthetic / Mood, precisely locating the "soul dimension"
• Preserve Feel, Replace Content: Remix = swap content, keep the soul
• Ultra-Lightweight Operation: Send one image + say one sentence -> get output, results first then iterate

Conventions

• Intermediate artifacts are stored in ./.image-remix/{session_name}/ (session_name derived from image filename, lowercased with special characters removed)
• No collages/grids: Each generation call produces only 1 image. Never include "grid," "collage," "2x2," etc. in prompts
• ⚠️ MJ Four-Grid Note: MJ always outputs a 2x2 four-grid; the user crops it on the canvas themselves
• ⚠️ Do NOT pass reference images to text-to-image tools: The reference image is only used for Phase 1 analysis; generation relies entirely on text prompts to avoid copyright risks

---

Pipeline

Phase 0: Input  →  Phase 1: Decompose  →  Phase 2: Quick Select  →  Phase 3: Generate  →  Phase 4: Iterate  →  Phase 5: Output

---

Phase 0: Input

Supported: local path / URL (download with import_images) / search description (use image_search).

Multiple images: analyze separately -> extract each image's soul dimension -> merge into a combined prompt (e.g., "Image A's composition + Image B's color palette") -> inform the user then generate.

File structure:

.image-remix/{session_name}/
├── decompose.json       # Phase 1 analysis results
├── generation_log.md    # Generation log
└── outputs/             # Generated images v1_01.png …

---

Phase 1: Decompose

1a. Origin Tracing

Use read_media to analyze the original image's origin, cross-referencing visual fingerprints in references/model-fingerprints.md:

read_media(
  file_path=reference image path,
  question="Determine which AI model / camera / hand-drawn this image most likely comes from.
  Cross-reference the visual fingerprints in model-fingerprints.md one by one.
  Focus on: skin rendering, highlight reflections, edge blending quality, color tendencies, overall AI feel.
  Output: model_guess, confidence(0-1), clues(at least 3 specific pieces of evidence),
          alt_guess, is_ai_generated, is_photo, is_illustration"
)

1b. 10-Dimension Analysis

read_media(
  file_path=reference image path,
  question="Deeply analyze this image across the following 10 dimensions, providing for each:
  description (English technical description), summary (Chinese summary), score (0-1 salience):
  1.Composition 2.Art Style 3.Color (including palette hex values) 4.Lighting 5.Atmosphere
  6.Texture 7.Subject 8.Narrative 9.Post-processing Style 10.Medium/School"
)

1c. Collapse to Form / Aesthetic / Mood

Dimension	Underlying Components	Meaning
Form	Composition + Subject	What is depicted and how it's arranged
Aesthetic	Art Style + Color + Texture + Post-processing + Medium	What painting style and tonal quality
Mood	Atmosphere + Lighting + Narrative	What feeling and emotion

Take the weighted average of sub-dimension scores to identify 1-2 soul dimensions (the most distinctive ones).

1d. Write to decompose.json

Merge origin + dimensions + collapsed + soul fields and write to file.

---

Phase 2: Quick Select

Display Origin Conclusion (mandatory)

📍 Origin Conclusion
  Image Source: [model_guess] (confidence [confidence])
  Evidence: [2-3 most critical clues]
  Soul Dimension: [soul_summary]

🎯 Direct Call: [matched tool] — [one-sentence explanation why]
  Prompt Style: [writing strategy for this model]
  Fallback: [what to use if tool is unavailable]

Origin -> Tool + Prompt Style Mapping Table (origin directly determines which tool and style to use; the two are inseparable):

Origin Source	Tool to Call	Prompt Style	Fallback
Seedream	Seedream image generation tool	Realistic long description, precise facial features/clothing materials, refined lighting and atmosphere	all_in_one, keep style
Kolors	Kolors image generation tool	Realistic description, emphasize highlight-material contrast	all_in_one
Hunyuan	Hunyuan image generation tool	Realistic + Chinese aesthetic vocabulary, concise with breathing room	all_in_one
Jimeng	Jimeng image generation tool	Direct description, explicit style keywords, write out saturation levels	all_in_one
Wanx / Tongyi Wanxiang	Wanx image generation tool	Concise description, avoid overly dense detail stacking	all_in_one
Midjourney v5/v6	MJ image generation tool	Keyword stacking + style tags, concise and not verbose	all_in_one, keep keyword style
Flux.1	Flux image generation tool	Natural language long sentences, detailed lighting and material description	all_in_one, keep long description
Stable Diffusion	SD image generation tool	Supports weight syntax (word:1.3), negative prompt written separately	all_in_one, remove weights and switch to natural language
DALL-E 3	DALL-E image generation tool	Natural language, straightforward description, avoid over-stylization	all_in_one
Ideogram	Ideogram image generation tool	Specify text content and layout requirements clearly	all_in_one
Real photograph	High-realism image generation tool	Photography terminology dominant, lens parameters + film stock	all_in_one, keep photography terminology
Hand-drawn / Illustration	Illustration image generation tool	Medium + school as anchor	all_in_one, keep medium description
Generic AI / Hard to determine	all_in_one_image_generation	Keywords + natural language hybrid	No fallback needed
Completely uncertain	Multiple tools, one image each for comparison	Use each tool's optimal prompt style	—

Fallback rule when tool is unavailable: Fall back to all_in_one_image_generation, but keep the original tool's prompt writing style unchanged, preserving the style DNA as much as possible.

Generation Path Selection (must ask)

Ask the user via Q&A:

• Text-to-Image (recommended): Pure text prompt, zero copyright risk
• Image-to-Image: Reference image passed as image_ref, higher fidelity, user must confirm copyright risk

Content Direction Confirmation

Directly ask the user "What do you want to create?" — a single sentence is enough to proceed to generation.

If the user has no direction (only says "help me remix"), recommend 3 replacement directions based on the soul dimension for selection.

Quick Commands: Reskin (swap subject only) / Extract Style (preserve Aesthetic) / Extract Composition (preserve Form) / Extract Mood (preserve Mood)

---

Phase 3: Generate

Branch A: Text-to-Image

Strictly prohibit passing the reference image to the generation tool. The prompt is entirely reconstructed based on Phase 1 analysis.

Prompt Construction:

[New content subject]. [English description of preserved dimensions]. single subject, one image only, no grid, no collage, no text, no watermark

Dimension -> Prompt Focus:

Preserved Dimension	Prompt Emphasis
Form	Camera angle, shot scale, subject position, depth layers
Aesthetic	Art school, hex values/color relationships, medium description, color grading reference
Mood	Emotion adjectives, light source description, cultural/era references, metaphorical language

Branch B: Image-to-Image

Reference image passed as image_ref; prompt focuses on describing the new content direction, with style description as supplementary guidance.

Generation Parameters

Ask the user for size: Follow Original (default, measure with ffprobe then map) / 1:1 / 16:9 / 9:16

"Follow Original" mapping rules: ratio > 1.5 -> 16:9; 0.8~1.2 -> 1:1; < 0.8 -> 9:16. Must measure first then write to task_description; guessing is prohibited.

Default generation: 4 variants, each called separately, with slight prompt variations to maintain diversity.

Save output to .image-remix/{session_name}/outputs/v{version}_{index}.png, and synchronously update generation_log.md.

---

Phase 4: Iterate

After displaying results, ask about satisfaction: Satisfied, finish / Fine-tune / Change direction / Switch model.

Fine-tuning adjusts at the prompt level directly, without going back to Phase 1 for re-analysis:

Feedback	Action
"Make the colors cooler"	Fine-tune color prompt words
"Change composition to close-up"	Adjust camera parameters
"Style is too different"	Strengthen style description or switch model
"This one's composition + that one's color"	Combine dimensions from two images and regenerate

---

Phase 5: Output

Delivery checklist: file location / total generated / iteration rounds / soul dimension / origin source / prompt writing strategy

Optional: CDN upload / style library entry (save to .image-remix/style-library/{style name}.md) / continue generating variants

Style library format (see references/analysis-example.md for an example):

# {Style Name}
## Origin
- Image source / tool called / prompt writing strategy
## Soul Dimension
- Soul: {Form/Aesthetic/Mood} — {soul_summary}
## Successful Prompt
{complete English prompt}
## Dimension Snapshot
- Form / Aesthetic / Mood