Mmcp.market

muapi-color-analysis-board skill

by SamurAIGPT·SamurAIGPT/Generative-Media-Skills·4.3k stars·MIT

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.

A100/100content scan

Is the muapi-color-analysis-board skill safe?

Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-09-28.

No findings.

Install the muapi-color-analysis-board skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/SamurAIGPT/Generative-Media-Skills.git /tmp/Generative-Media-Skills
mkdir -p ~/.claude/skills
cp -r /tmp/Generative-Media-Skills/library/visual/color-analysis-board ~/.claude/skills/muapi-color-analysis-board
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

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

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 MUAPIAPIKEY 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/ -H "x-api-key: $MUAPIAPIKEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait .
  • 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.

More skills from SamurAIGPT/Generative-Media-Skills

  • Amuapi-3d-logo-animationTransform a 2D logo into a premium 3D version and animate it with professional cinematic effects.
  • Amuapi-action-figure-generatorConvert a photo of a person into a custom 3D action figure, complete with collectible toy packaging.
  • Amuapi-ad-creativeGenerate a high-converting ad creative set — hero image, ad copy variations, and platform-optimized crops for Meta, Google Display, and LinkedIn.
  • Amuapi-ad-creativeGenerate a high-converting ad creative set — hero image, ad copy variations, and platform-optimized crops for Meta, Google Display, and LinkedIn.
  • Amuapi-ai-clippingTurn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's `/ai-clipping` endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe, and vertical face-tracking auto-crop server-side. No local Whisper, no local LLM, no GPU.
  • Amuapi-ai-clippingTurn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's `/ai-clipping` endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe, and vertical face-tracking auto-crop server-side. No local Whisper, no local LLM, no GPU.
  • Amuapi-ai-fight-sceneGenerate a high-cut-density action / fight scene by first composing a 16-cell storyboard image, then driving Seedance 2.0 image-to-video off that storyboard. Stacks GPT-Image-2 (character sheet + storyboard), Nano-Banana-2 (environment concept), and Seedance 2.0 i2v.
  • Amuapi-amazon-product-listingGenerate a complete Amazon product listing image set — hero image, lifestyle shot, infographic with features, and comparison/detail closeups optimized for Amazon standards.
  • Amuapi-animal-video-generatorCreate a hilarious and ultra-realistic video of an anthropomorphic animal acting like a human vlogger in a real-world setting.
  • Amuapi-award-ceremony-videoGenerate a 15-second cinematic awards-ceremony video — a host announces a winner from the stage, a spotlight finds them in the crowd, they walk up to the podium, receive the award, and the LED display reveals their name and "THE BEST ACTOR".
  • Amuapi-blog-headerCreate a professional, eye-catching blog post header image sized for web (1200×628) with optional title composition guidance.
  • Amuapi-brand-kitGenerate a cohesive brand visual kit — logo concept, color palette moodboard, and typography pairing suggestions.

All agent skills → · MCP servers