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gif-sticker-maker

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Convert photos (people, pets, objects, logos) into 4 animated GIF stickers with captions. Use when: user wants to create cartoon stickers, GIF expressions, emoji packs, animated avatars, or convert photos to Funko Pop / Pop Mart blind box style animations. Triggers: sticker, GIF, cartoon, emoji, expression pack, avatar animation.

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How to use this skill

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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/HHU3637kr/skills/blob/HEAD/gif-sticker-maker/SKILL.md

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GIF Sticker Maker

Convert user photos into 4 animated GIF stickers (Funko Pop / Pop Mart style).

Style Spec

  • Funko Pop / Pop Mart blind box 3D figurine
  • C4D / Octane rendering quality
  • White background, soft studio lighting
  • Caption: black text + white outline, bottom of image

Prerequisites

Before starting any generation step, ensure:

  1. Python venv is activated with dependencies from requirements.txt installed
  2. MINIMAX_API_KEY is exported (e.g. export MINIMAX_API_KEY='your-key')
  3. ffmpeg is available on PATH (for Step 3 GIF conversion)

If any prerequisite is missing, set it up first. Do NOT proceed to generation without all three.

Workflow

Step 0: Collect Captions

Ask user (in their language):

"Would you like to customize the captions for your stickers, or use the defaults?"

  • Custom: Collect 4 short captions (1–3 words). Actions auto-match caption meaning.
  • Default: Look up captions table by detected user language. Never mix languages.

Step 1: Generate 4 Static Sticker Images

Tool: scripts/minimax_image.py

  1. Analyze the user's photo — identify subject type (person / animal / object / logo).
  2. For each of the 4 stickers, build a prompt from image-prompt-template.txt by filling {action} and {caption}.
  3. If subject is a person: pass --subject-ref <user_photo_path> so the generated figurine preserves the person's actual facial likeness.
  4. Generate (all 4 are independent — run concurrently):
python3 scripts/minimax_image.py "<prompt>" -o output/sticker_hi.png --ratio 1:1 --subject-ref <photo>
python3 scripts/minimax_image.py "<prompt>" -o output/sticker_laugh.png --ratio 1:1 --subject-ref <photo>
python3 scripts/minimax_image.py "<prompt>" -o output/sticker_cry.png --ratio 1:1 --subject-ref <photo>
python3 scripts/minimax_image.py "<prompt>" -o output/sticker_love.png --ratio 1:1 --subject-ref <photo>

--subject-ref only works for person subjects (API limitation: type=character). For animals/objects/logos, omit the flag and rely on text description.

Step 2: Animate Each Image → Video

Tool: scripts/minimax_video.py with --image flag (image-to-video mode)

For each sticker image, build a prompt from video-prompt-template.txt, then:

python3 scripts/minimax_video.py "<prompt>" --image output/sticker_hi.png -o output/sticker_hi.mp4
python3 scripts/minimax_video.py "<prompt>" --image output/sticker_laugh.png -o output/sticker_laugh.mp4
python3 scripts/minimax_video.py "<prompt>" --image output/sticker_cry.png -o output/sticker_cry.mp4
python3 scripts/minimax_video.py "<prompt>" --image output/sticker_love.png -o output/sticker_love.mp4

All 4 calls are independent — run concurrently.

Step 3: Convert Videos → GIF

Tool: scripts/convert_mp4_to_gif.py

python3 scripts/convert_mp4_to_gif.py output/sticker_hi.mp4 output/sticker_laugh.mp4 output/sticker_cry.mp4 output/sticker_love.mp4

Outputs GIF files alongside each MP4 (e.g. sticker_hi.gif).

Step 4: Deliver

Output format (strict order):

  1. Brief status line (e.g. "4 stickers created:")
  2. <deliver_assets> block with all GIF files
  3. NO text after deliver_assets
<deliver_assets>
<item><path>output/sticker_hi.gif</path></item>
<item><path>output/sticker_laugh.gif</path></item>
<item><path>output/sticker_cry.gif</path></item>
<item><path>output/sticker_love.gif</path></item>
</deliver_assets>

Default Actions

#ActionFilename IDAnimation
1Happy wavinghiWave hand, slight head tilt
2Laughing hardlaughShake with laughter, eyes squint
3Crying tearscryTears stream, body trembles
4Heart gestureloveHeart hands, eyes sparkle

See references/captions.md for multilingual caption defaults.

Rules

  • Detect user's language, all outputs follow it
  • Captions MUST come from captions.md matching user's language column — never mix languages
  • All image prompts must be in English regardless of user language (only caption text is localized)
  • <deliver_assets> must be LAST in response, no text after