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gif-sticker-maker · minimax-ai — Claude Code skill: turn photos into animated GIF

A skill that converts a photo into 4 animated GIF stickers in Funko Pop style with captions. Use it to create expressive stickers, emoji packs, or animated avatars for messengers.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add MiniMax-AI/skills --skill gif-sticker-maker -a claude-code
Open on GitHub

What gif-sticker-maker does

gif-sticker-maker analyzes an uploaded photo, identifies the subject type (person, animal, object, logo), and generates four stickers: happy, laughing, crying, and in-love. Each sticker is a 3D figurine in Pop Mart blind-box style, rendered with C4D quality, on a white background with soft studio lighting.

The skill uses MiniMax Image Generation API to create static images and MiniMax Video Generation API to animate them. It generates four images in step one, animates each to video in step two, and converts videos to GIF in step three. For human subjects, the skill preserves facial features via the --subject-ref flag; for animals and objects, it relies on text descriptions.

Before running, activate a Python venv with dependencies from requirements.txt, export MINIMAX_API_KEY, and ensure ffmpeg is on PATH. All four images and videos are generated in parallel, so total time depends on API response speed.

What it helps with

  • convert a photo into animated Funko Pop stickers
  • create a set of GIF expressions for a messenger or chat app
  • generate an emoji pack with movement and animation
  • turn a pet or character photo into a playful avatar
  • animate a logo or object in blind-box collectible style

Example prompts for the agent

  • Turn my photo into four fun stickers with emotions: happy, laughing, crying, and in love
  • Create a set of GIF stickers of my cat in Pop Mart style with captions in English
  • Make four animated avatars from this company logo photo

How to install gif-sticker-maker

1Skills CLI (Vercel)

npx skills add MiniMax-AI/skills --skill gif-sticker-maker -a claude-code

2Manually: put the files in place

~/.claude/skills/gif-sticker-maker/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/gif-sticker-maker/

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Questions about gif-sticker-maker

How do I install gif-sticker-maker in Claude Code?

Run npx skills add MiniMax-AI/skills --skill gif-sticker-maker -a claude-code, then find the installed skill at ~/.claude/skills/gif-sticker-maker/SKILL.md.

What does gif-sticker-maker do?

The skill analyzes a photo and creates four animated GIF stickers in Funko Pop style (happy, laughing, crying, in love) with captions. Each sticker is a 3D figurine with soft studio lighting.

What do I need to get it working?

Activate a Python venv with packages from requirements.txt, set the MINIMAX_API_KEY environment variable, and have ffmpeg installed.

Source text

SKILL.md · MIT
---
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 API
---

# 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](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**):

```bash
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:

```bash
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`

```bash
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**

```xml
<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

© MiniMax-AI · MIT · MiniMax-AI/skills

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