/gif-sticker-maker
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,
Claude Code
$ npx -y skills add poco-ai/poco-claw --skill gif-sticker-maker --agent claude-code
Codex
$ npx skills add poco-ai/poco-claw --skill gif-sticker-maker -a codex -y
Cursor
$ npx skills add poco-ai/poco-claw --skill gif-sticker-maker -a cursor -y
Gemini CLI
$ npx skills add poco-ai/poco-claw --skill gif-sticker-maker -a gemini-cli -y
GitHub Copilot
$ npx skills add poco-ai/poco-claw --skill gif-sticker-maker -a github-copilot -y
OpenCode
$ npx skills add poco-ai/poco-claw --skill gif-sticker-maker -a opencode -y
Windsurf
$ npx skills add poco-ai/poco-claw --skill gif-sticker-maker -a windsurf -y
SKILL.md
gif-sticker-maker.SKILL.mdname: gif-sticker-maker
description: |
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.
license: MIT
metadata:
version: "1.2"
category: creative-tools
style: Funko Pop / Pop Mart
output_format: GIF
output_count: 4
sources:
- MiniMax Image Generation API
- MiniMax Video Generation APIGIF 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](references/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](references/captions.md) 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](assets/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](assets/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
| # | 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](references/captions.md) for multilingual caption defaults.
Rules
- Detect user's language, all outputs follow it
- Captions MUST come from [captions.md](references/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
Read more
name: gif-sticker-maker
description: |
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.
license: MIT
metadata:
version: "1.2"
category: creative-tools
style: Funko Pop / Pop Mart
output_format: GIF
output_count: 4
sources:
- MiniMax Image Generation API
- MiniMax Video Generation APIGIF 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](references/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](references/captions.md) 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](assets/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](assets/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
| # | 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](references/captions.md) for multilingual caption defaults.
Rules
- Detect user's language, all outputs follow it
- Captions MUST come from [captions.md](references/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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Questions about gif-sticker-maker.
- Which coding agents can use gif-sticker-maker?
- gif-sticker-maker installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

