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muapi-color-analysis-board

Turn a portrait photo into a high-end editorial "Color Analysis Board" in a luxury fashion-magazine style (Dior / Ralph Lauren aesthetic) — best colors, undertone, makeup guide, capsule wardrobe, hair & jewelry recommendations, all laid out on a clean beige/ivory grid.

Quellinformationen

Repository
SamurAIGPT/Generative-Media-Skills
Letzte Quellaktivität
19. Mai 2026 um 13:11
Erkannte Sprache von SKILL.md
Englisch
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4.339
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496

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
slug
muapi-color-analysis-board
name
muapi-color-analysis-board
version
1.0.0
description
Turn a portrait photo into a high-end editorial "Color Analysis Board" in a luxury fashion-magazine style (Dior / Ralph Lauren aesthetic) — best colors, undertone, makeup guide, capsule wardrobe, hair & jewelry recommendations, all laid out on a clean beige/ivory grid.
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true
# Color Analysis Board **Turn a portrait photo into a high-end editorial "Color Analysis Board" in a luxury fashion-magazine style (Dior / Ralph Lauren aesthetic) — best colors, undertone, makeup guide, capsule wardrobe, hair & jewelry recommendations, all laid out on a clean beige/ivory grid.** ## Inputs | Name | Type | Required | Default | Description | |:---|:---|:---|:---|:---| | `person_image` | image_url | yes | — | A clear, well-lit portrait of the person. Front-facing, neutral background, and natural lighting give the strongest color reads (undertone, hair, eyes). Avoid heavy filters or makeup that masks the natural complexion. | ## Steps ### Phase A — Color Analysis Board Generation If `{{person_image}}` is not provided, ask the user to upload a clear front-facing portrait. Make sure the face is well-lit with natural color (no heavy filters, color-cast lighting, or sunglasses) — the model needs accurate skin, hair, and eye color to pick the right palette. Once the photo is available, submit ONE step to generate the color analysis board: 1. **Color Analysis Board Generation** — `muapi image edit` (model=`gpt-image-2-image-to-image`): - Reference Image: `{{person_image}}` - Image size: `3840x2160` (16:9 landscape) — magazine-spread aspect ratio - Background: `auto` - Output format: `png` - Quality: `auto` - Moderation: `low` - Prompt: ``` Create a high-end editorial "Color Analysis Board" from this portrait in a luxury fashion magazine style (Dior / Ralph Lauren aesthetic). Clean beige/ivory background, warm tones, soft diffused lighting, ultra-detailed photorealistic quality, consistent lighting, minimal elegant typography, grid-based layout. Main portrait: enhanced natural beauty (same identity, smooth skin, soft glow, realistic texture) Top section: "Your Best Colors" with fabric swatches with the best algorithm choices Undertone panel: warm / neutral / cool with marked result. Colors to avoid Neutrals that work Prints that flatter Makeup guide: eyeshadows, blush, lips, highlighter "You in your colors": multiple outfit best variations Hair colors: best. Jewelry Style notes Capsule wardrobe: coordinated outfits, shoes, bags, accessories Style: best style for me ``` Present the generated board to the user. Suggest variations they can try: a different source portrait (different lighting / hairstyle for comparison), or asking to bias the palette toward a season (e.g. "spring warm" vs "winter cool") or a specific brand aesthetic (e.g. minimalist Scandinavian, Old Money, streetwear). ## Trigger Keywords `color analysis`, `color analysis board`, `personal color palette`, `seasonal color analysis`, `undertone analysis`, `style guide board`, `fashion color board`, `capsule wardrobe board` --- ## Notes for the Executing Agent - This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call `muapi` CLI commands. Use `muapi auth configure` first if `MUAPI_API_KEY` is unset. - For model IDs without a CLI alias yet, fall back to the raw endpoint via `curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'` and poll with `muapi predict wait <request_id>`. - Substitute `{{input_name}}` placeholders with the user's actual inputs before issuing each call. - Source schema reference: `gpt-image-v2-edit` (from the source workflow JSON) maps to `gpt-image-2-image-to-image` in the muapi catalog. - The output is intentionally 16:9 (3840×2160) so it reads as a magazine spread / desktop wallpaper / Pinterest landscape board. For IG-feed square or 9:16 vertical, request a re-crop or re-run with a different `image_size`.
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