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Gif sticker maker

Skill martgueritainaccurate875/skills/skills/gif-sticker-maker

Power AI coding agents with structured skills for frontend, fullstack, mobile, and shader development

Install

npx -y skills add martgueritainaccurate875/skills --skill 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.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

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:

Python venv is activated with dependencies from requirements.txt installed
MINIMAX_API_KEY is exported (e.g. export MINIMAX_API_KEY='your-key')
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

Analyze the user's photo — identify subject type (person / animal / object / logo).
For each of the 4 stickers, build a prompt from image-prompt-template.txt by filling {action} and {caption}.
If subject is a person: pass --subject-ref <user_photo_path> so the generated figurine preserves the person's actual facial likeness.
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):

Brief status line (e.g. "4 stickers created:")
<deliver_assets> block with all GIF files
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

#	Action	Filename ID	Animation
1	Happy waving	hi	Wave hand, slight head tilt
2	Laughing hard	laugh	Shake with laughter, eyes squint
3	Crying tears	cry	Tears stream, body trembles
4	Heart gesture	love	Heart 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

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