Mmcp.market

muapi-chibi-collage-effect skill

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

Turn a real lifestyle photo into a polished "chibi clone sticker diary" image — the original person stays photorealistic, surrounded by 5–8 kawaii chibi mini-clones, scrapbook doodles, and handwritten-style captions that match the scene.

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Install the muapi-chibi-collage-effect 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/chibi-collage-effect ~/.claude/skills/muapi-chibi-collage-effect
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

Chibi Collage Effect

Turn a real lifestyle photo into a polished "chibi clone sticker diary" image — the original person stays photorealistic, surrounded by 5–8 kawaii chibi mini-clones, scrapbook doodles, and handwritten-style captions that match the scene.

Inputs

Steps

Phase A — Chibi Collage Generation

If {{person_image}} is not provided, ask the user to upload a lifestyle photo (café, outdoor, cozy at home, travel, etc.). The scene context is what makes the chibi clones feel native to the moment, so a generic studio headshot will give weaker results than a real lifestyle shot.

Once the photo is available, submit the plan with ONE step to generate the chibi collage:

  1. Chibi Collage Generation — muapi image edit (model=gpt-image-2-image-to-image):
  • Reference Image: {{person_image}}
  • Image size: 2160x3840 (9:16 portrait) — high-resolution social-media-ready output
  • Background: auto
  • Output format: png
  • Quality: auto
  • Moderation: low
  • Prompt:
Create a high-quality "chibi clone sticker diary photo" based on the uploaded real-life image. Preserve the original person's identity, face, hairstyle, hair color, outfit, body proportions, pose, lighting, and background. Do not alter facial features or turn the subject into a full illustration—maintain a realistic photo look.
     Analyze the uploaded image carefully: identify the setting, mood, activity, clothing style, and overall vibe of the scene. Use this analysis to determine the theme of the chibi stickers, poses, emotions, and text phrases — everything should feel native to the actual moment captured in the photo.
     Add 5–8 chibi mini clones of the same person around the subject, designed in a consistent kawaii sticker style (big head, small body, large expressive eyes, clean digital finish). Each clone must clearly resemble the real person (same hair, outfit, colors).
     Design each chibi with different actions and emotions that are directly relevant to what the person is doing or feeling in the photo — inferred naturally from the scene (e.g. if they're at a café: sipping coffee, reading, daydreaming, chatting; if outdoors: exploring, laughing, taking photos; if coz

Present the generated chibi collage to the user. Suggest variations they can try: different source photos (travel, café, cozy-at-home), or asking to bias the captions toward a specific tone (cute, sassy, journal-style).

Trigger Keywords

chibi collage, chibi sticker diary, mini me stickers, kawaii clone collage, sticker diary photo, scrapbook chibi

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 maps to gpt-image-2-image-to-image in the muapi catalog.
  • The output is intentionally 9:16 (2160×3840) so it's ready for IG Stories / Reels / TikTok / YT Shorts without re-cropping.

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