muapi-color-analysis-board

Original：🇺🇸 English

Translated

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.

3installs

Sourcesamuraigpt/generative-media-skills

Added on2026-05-19

NPX Install

npx skill4agent add samuraigpt/generative-media-skills muapi-color-analysis-board

SKILL.md Content

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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:

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
```
.