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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, GIF, cartoon, emoji, expression pack, avatar animation.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=minimax-ai-skills-skills-gif-sticker-maker-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
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: 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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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
同じスキルを各プラットフォーム形式で出力できます。
.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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