自动广告生成器

Generate professional advertisement posters for multiple industries including automotive, cultural tourism, fragrance, tea, and more. Create commercial layou...

Security Scan

The skill mostly does what it claims (ad/poster generation), but there are mismatches between declared requirements and actual code and a risky install recommendation (curl|bash) that make the package suspicious and worth manual review before installing.

Purpose & Capability

The declared requirements (Dreamina CLI and remove.bg key) generally align with an ad-generation tool that can call an AI image service and remove backgrounds. However, SKILL.md marks remove.bg as optional while the registry requires REMOVE_BG_API_KEY — a mismatch. The code also references other AI backends (OpenAI/DALL·E) which are described as optional, but those APIs are invoked in code even though their credentials (e.g., OPENAI_API_KEY) are not declared in the skill metadata.

Instruction Scope

The runtime instructions and code call external CLIs and APIs (dreamina, and code paths that call OpenAI / DALL·E and requests). SKILL.md instructs installing 'dreamina' via a curl|bash one-liner hosted at jimeng.jianying.com. The code will call subprocesses (dreamina text2image, query_result, etc.) and may attempt to contact external services — some of which (OpenAI) are not declared as required env vars. The instructions and code also reference background removal though the implementation for that in the repository is incomplete/inconsistent. Overall the runtime behavior reaches outside the local system to third-party endpoints and relies on undeclared credentials.

Install Mechanism

There is no formal install spec in the registry, but SKILL.md tells the user to run: curl -s https://jimeng.jianying.com/cli | bash to install dreamina. Piping an external script into bash from a third-party domain is high risk. package.json also lists an optionalDependency pointing to https://jimeng.jianying.com/cli rather than a well-known package registry. These indicate the skill expects you to run remote installer code from a single domain that is not a widely vetted release host.

Credentials

The registry requires DREAMINA_API_KEY and REMOVE_BG_API_KEY. DREAMINA_API_KEY is proportionate. REMOVE_BG_API_KEY is declared required but SKILL.md calls it optional. More importantly, the code contains a path that uses the OpenAI client (generate_with_dalle) yet OPENAI_API_KEY (or equivalent) is not declared in requires.env. The code also imports requests and openai at runtime but package.json only lists Pillow — missing dependency declarations and undeclared credentials increase the risk of silent failures or unexpected network calls.

Persistence & Privilege

The skill is not always-enabled, does not request elevated or system-wide configuration changes, and writes outputs to local temp and output directories. It does not modify other skills or global agent settings. Its persistence and privileges appear normal for a user-run tool.

What to consider before installing

What to consider before installing: - Do not run curl | bash installers from unknown domains without inspection; the README recommends piping a script from jimeng.jianying.com to install the Dreamina CLI — this is the highest-risk action here. Prefer installing CLIs from official release pages or package managers and review the installer content first. - The skill expects DREAMINA_API_KEY (reasonable) and REMOVE_BG_API_KEY (declared required but marked optional in docs). The code also calls OpenAI (DALL·E) but does not declare OPENAI_API_KEY — ask the author to clarify required environment variables. - Dependencies are incomplete: package.json only lists Pillow but code imports requests and openai. Running the code may fail or silently attempt to reach external services. Review and install dependencies in a controlled environment (container or sandbox). - Review the code paths that call subprocess.run(['dreamina', ...]) to ensure the Dreamina CLI used is the official binary you trust; if you must use Dreamina, install it from a vetted source and confirm its behavior. - If you handle sensitive images or credentials, avoid giving API keys to third-party services you don't control. Consider running the PIL-only path (local generation) if you want to avoid remote AI services. - If you want to proceed: ask the publisher to (1) remove the curl|bash recommendation or replace it with a vetted install guide, (2) declare all required env vars (including OPENAI_API_KEY if used), and (3) add missing runtime dependencies to package.json. Otherwise run the tool in an isolated environment and audit network activity.

Auto Ad Generator

Generate professional advertisement posters with AI-powered backgrounds and product compositing.

依赖声明 (Dependencies)

本 Skill 需要以下外部服务和工具：

必需的二进制文件

• python3 - Python 3.8+
• dreamina - Dreamina CLI (通过 curl -s https://jimeng.jianying.com/cli | bash 安装)

必需的环境变量

• DREAMINA_API_KEY - Dreamina API 密钥
• REMOVE_BG_API_KEY - remove.bg API 密钥（可选，用于背景移除）

可选 API 服务

• DALL-E / Midjourney / Stability AI - 用于 AI 图像生成
• Dreamina/即梦 - 主要 AI 生成后端
• remove.bg - 产品图背景移除

---

Overview

This skill supports multiple industries and platforms:

• Industries: Automotive, cultural tourism, fragrance/beauty, tea, recruitment, public welfare
• Platforms: WeChat official accounts (21:9), Xiaohongshu (3:4), airport displays (16:9/9:16), lightboxes
• Backends: PIL (local/free) or Dreamina/即梦 CLI (AI-powered, high quality)

Quick Start

Generate an Ad

# Using Dreamina AI backend
python main.py --backend dreamina \
  --car ./product.jpg \
  --brand "Brand Name" \
  --subtitle "Product Tagline" \
  --slogan "Marketing Slogan" \
  --platform xiaohongshu \
  --style premium \
  --output ./output

# Using PIL (local, free)
python main.py --backend pil \
  --car ./product.jpg \
  --brand "Brand Name" \
  --output ad.jpg

Interactive Mode

python main.py
# Follow prompts to select backend, platform, and style

Core Workflow

1. Analyze Input

When user provides car images and requests:

• Identify car type: sedan, SUV, MPV, etc.
• Extract key features: color, design highlights, target audience
• Determine ad style: luxury, sporty, family-friendly, tech-focused

2. Gather Requirements

Ask the user (unless provided):

1. Brand name and model?
2. Main headline/slogan?
3. Subtitle/description?
4. Target audience? (young professionals, families, etc.)
5. Celebrity endorser image? (optional)
6. Preferred color scheme? (or auto-detect from brand)

3. Generate Ad Components

Background Generation

Use image generation to create gradient background:

Prompt template:
"Premium gradient background for car advertisement, 
{primary_color} to {secondary_color} smooth gradient, 
subtle light rays, luxury automotive aesthetic, 
minimalist, high-end commercial photography style, 
no text, no car, clean background only"

Car Subject Enhancement

• Clean up the car image (remove background if needed)
• Enhance lighting and reflections
• Position car at 3/4 front angle or side profile

Typography Layout

Layout Structure (1080x1920 vertical):
┌─────────────────┐
│   HEADLINE      │ ← 40-60px, bold, white or contrast color
│   subtitle      │ ← 20-28px, lighter weight
│                 │
│   [CAR IMAGE]   │ ← Main visual, 60% of frame
│   [Celebrity]   │ ← Optional, overlapping or beside
│                 │
│   Slogan        │ ← Bottom area
│   Logo          │ ← Corner placement
└─────────────────┘

4. Style Reference: Li Auto Aesthetic

Color Palettes:

• Premium: Deep blue → Purple gradient (#1a237e → #7c4dff)
• Warm: Orange → Pink gradient (#ff6b35 → #f7931e)
• Cool: Teal → Cyan gradient (#00897b → #00bcd4)
• Dark: Black → Deep gray with subtle blue tint

Typography:

• Headline: Bold, condensed sans-serif
• Subtitle: Light weight, generous letter-spacing
• Slogan: Italic or script for emotional touch

Lighting:

• Soft, diffused key light
• Subtle rim light on car edges
• Gradient background with light source from top

5. Execution Steps

# Pseudo-code for skill execution
def generate_car_ad(car_image, params):
    # Step 1: Analyze car
    car_analysis = analyze_image(car_image)
    
    # Step 2: Generate background
    background = generate_image(
        prompt=build_background_prompt(params['style']),
        size="1024x1536"
    )
    
    # Step 3: Process car image
    car_processed = remove_background(car_image)
    car_enhanced = enhance_lighting(car_processed)
    
    # Step 4: Composite
    composite = overlay_car_on_background(
        background, 
        car_enhanced,
        position="center-bottom",
        scale=0.7
    )
    
    # Step 5: Add text
    final = add_typography(
        composite,
        headline=params['headline'],
        subtitle=params['subtitle'],
        slogan=params['slogan'],
        font_style=params['style']
    )
    
    # Step 6: Add logo
    if params.get('logo'):
        final = overlay_logo(final, params['logo'])
    
    return final

6. Quality Checklist

Before presenting to user:

• Car is the clear focal point
• Text is readable against background
• Color harmony between car and background
• Professional lighting on car
• Brand/logo placement is subtle but visible
• Overall composition follows rule of thirds

Example Outputs

Example 1: Li Auto Style SUV Ad

Input: SUV image, "理想i6", "新形态纯电五座SUV"
Output: Purple-blue gradient, car at 3/4 angle, large white text, celebrity placement

Example 2: Sporty Sedan Ad

Input: Sports sedan, "P7", "纯粹驾驶乐趣"
Output: Dark background with orange accent lighting, dynamic angle, bold typography

Example 3: Family MPV Ad

Input: Minivan, "MEGA", "全家人的幸福空间"
Output: Warm gradient, spacious composition, friendly tone, emphasis on interior space

Tools & Scripts

Required Tools

• Image generation (DALL-E, Midjourney, or local SD)
• Image editing (remove.bg API or local model)
• Text overlay (PIL/Pillow or similar)
• Image composition (layer blending)

Bundled Scripts

• scripts/generate_background.py - Generate gradient backgrounds
• scripts/composite_ad.py - Layer car, background, text
• scripts/typography.py - Add professional text layout

Guidelines

Do

• Match background color to car's personality (sporty=warm, luxury=cool)
• Keep text minimal - one headline, one subtitle max
• Ensure car lighting matches background light source
• Use high-resolution source images (min 1024px width)

Don't

• Overcrowd with too much text
• Use clashing colors (unless intentional for contrast)
• Place car too small in frame (should be 50-70% of composition)
• Ignore the brand's existing visual identity

Edge Cases

• No car image provided: Ask user to upload, or generate concept car
• Low resolution input: Upscale first, or use as thumbnail/concept only
• Multiple cars: Focus on hero car, use others as supporting elements
• Specific brand requirements: Follow brand guidelines over Li Auto style

Reference Materials

See references/ directory for:

• li_auto_examples.md - Analysis of Li Auto ad patterns
• color_palettes.json - Pre-defined gradient combinations
• typography_guide.md - Font pairing recommendations
• composition_templates/ - Layout reference images

---

Dreamina (即梦) Integration

This skill supports Dreamina CLI for AI-powered background generation with higher quality results.

Prerequisites

# Install Dreamina CLI
curl -s https://jimeng.jianying.com/cli | bash

# Login (required before use)
dreamina login --headless

Two Backend Modes

Mode 1: PIL (Local, Free)

Uses Python PIL to generate simple gradient backgrounds.

• Pros: No API cost, instant, offline
• Cons: Basic quality, limited styles

python main.py --backend pil --car image.jpg --brand 理想 --model i6

Mode 2: Dreamina (AI-powered)

Uses Dreamina's text2image for professional AI backgrounds.

• Pros: High quality, diverse styles, professional aesthetics
• Cons: Consumes credits (~10-50 per image)

python main.py --backend dreamina --car image.jpg --brand 理想 --model i6 \
  --platform xiaohongshu --style premium

Platform Presets

Platform	Ratio	Size	Use Case
wechat	21:9	~900×383	公众号头图
xiaohongshu	3:4	1242×1660	小红书封面
airport_h	16:9	1920×1080	机场横屏广告
airport_v	9:16	1080×1920	机场竖屏广告
lightbox	16:9	Custom	灯箱广告

Style Presets

Style	Mood	Best For
premium	豪华科技	汽车、高端产品
warm	运动年轻	年轻品牌、运动产品
cool	环保现代	新能源、科技产品
dark	神秘高端	奢侈品、夜景
cultural	国风山水	文旅、传统文化
fragrance	粉金轻奢	美妆、香化
tea	禅意自然	茶叶、健康

Complete Workflow with Dreamina

# Step 1: Generate AI background
python main.py --backend dreamina \
  --car ./assets/suv.png \
  --brand 理想 \
  --model i6 \
  --subtitle "新形态纯电五座SUV" \
  --slogan "理想，就是活成自己喜欢的样子" \
  --platform xiaohongshu \
  --style premium \
  --output ./output

# Step 2: Check generation status
dreamina query_result --submit_id=<id_from_step1>

# Step 3: Download result and composite (manual or scripted)
# Step 4: Add typography using composite_ad.py

Credit Management

# Check remaining credits
dreamina user_credit

# Typical consumption:
# - text2image (2k): ~10-20 credits
# - text2image (4k): ~30-50 credits
# - image_upscale: ~20-40 credits

Advanced: Image-to-Image

Use existing image as base for style transfer:

from scripts.dreamina_backend import image_to_image

result = image_to_image(
    prompt="luxury car advertisement style, premium gradient background",
    image_path="existing_car_shot.jpg",
    ratio="16:9"
)