gif-sticker-maker

Savant verdict: Unsafe

Savant's security policy blocks importing this skill.

Live evaluation

Not evaluated yet. Workspaces can request a live evaluation.

Security assessment

17 patterns found

• Data Flow: requests.post( f"{API_BASE}/image_generation", headers=_headers(), json=payload, timeout=120, )critical · scripts/minimax_image.py:74 · Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.
• Data Flow: requests.post( f"{API_BASE}/video_generation", headers=_headers(), json=payload, timeout=30, )critical · scripts/minimax_video.py:98 · Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.
• Data Flow: requests.get( f"{API_BASE}/query/video_generation", headers=_headers(), params={"task_id": task_id}, timeout=30, )critical · scripts/minimax_video.py:118 · Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.
• Data Flow: requests.get( f"{API_BASE}/files/retrieve", headers=_headers(), params={"file_id": file_id}, timeout=30, )critical · scripts/minimax_video.py:148 · Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.
• MCP Least Privilege: Skill declares no tool scope ('permissions' or 'allowed-tools') but code capabilities were detected: env, network, shell.medium · SKILL.md:1 · Without declared permissions the skill's intent is opaque and cannot be validated.
• Dangerous Code Execution: subprocess.run( ["ffmpeg", "-y", "-i", input_path, "-vf", f"{scale_filter},palettegen=stats_mode=diff", palette], check=True, capture_output=True,medium · scripts/convert_mp4_to_gif.py:36 · subprocess module calls execute external commands. Without careful input validation, this enables command injection.
• Dangerous Code Execution: subprocess.run( ["ffmpeg", "-y", "-i", input_path, "-i", palette, "-lavfi", f"{scale_filter} [x]; [x][1:v] paletteuse=dither=bayer:bayer_scale=5:diff_mode=rectangle",medium · scripts/convert_mp4_to_gif.py:42 · subprocess module calls execute external commands. Without careful input validation, this enables command injection.
• Data Exfiltration: https://api.minimaxi.com/medium · scripts/minimax_image.py:22 · Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
• Data Exfiltration: https://api.minimaxi.com/medium · scripts/minimax_video.py:26 · Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
• Data Exfiltration: https://api.minimax.io/medium · scripts/minimax_image.py:23 · Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Structure

• Ships 3 executable scriptsscripts/convert_mp4_to_gif.py, scripts/minimax_image.py, scripts/minimax_video.py. Review what they do before enabling the skill for agents with tool access.

SKILL.md

---
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