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ad-ready-pro广告就绪专业版

Agent Skill

ad-ready-pro 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ad-ready-pro(广告就绪专业版)
来源仓库:https://github.com/pauldelavallaz/ad-ready-pro
安装命令:
openclaw skills install ad-ready-pro
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ad-ready-pro

简介

使用 ComfyDeploy 上的 Ad-Ready 管道从产品 URL 生成专业的广告图像。当用户想要通过提供 URL 来为任何产品创建广告时使用,还可以选择提供品牌简介(70 多个品牌)和漏斗阶段定位。支持模特/达人融合、品牌感知创意方向、多格式输出。与 Morpheus(手动时尚摄影)不同,Ad-Ready 是 URL 驱动、品牌智能和漏斗阶段感知的。

SKILL.md

name
ad-ready
description
Generate professional advertising images from product URLs using the Ad-Ready pipeline on ComfyDeploy. Use when the user wants to create ads for any product by providing a URL, optionally with a brand profile (70+ brands) and funnel stage targeting. Supports model/talent integration, brand-aware creative direction, and multi-format output. Differs from Morpheus (manual fashion photography) — Ad-Ready is URL-driven, brand-intelligent, and funnel-stage aware.

Ad-Ready: AI Advertising Image Generator

Generate professional advertising images from product URLs using a 4-phase AI pipeline on ComfyDeploy.

⚠️ CRITICAL: Required Inputs Checklist

Before running ANY ad generation, the agent MUST ensure ALL of these are provided:

InputRequired?How to Get It
--product-url✅ ALWAYSUser provides the product page URL
--product-image✅ ALWAYSDownload from the product page, or user provides
--logo✅ ALWAYSDownload from brand website or search online. MUST be an image file
--reference✅ RECOMMENDEDAn existing ad whose style we want to clone. Search online or use previously generated images
--brand-profile✅ NEVER EMPTYPick from catalog or run brand-analyzer first. NEVER leave as "No Brand" if a brand is known
--prompt-profile✅ ALWAYSChoose based on campaign objective
--aspect-ratioDefault: 4:5Change if needed for platform
--modelOptionalModel/talent face from catalog or user-provided

🚨 NEVER Skip These Steps:

  1. Product image — Download the main product photo from the product URL. The scraper is fragile; always provide a product image explicitly.
  2. Brand logo — Download the logo from the brand's official website or search for "{brand name} logo" online. Must be a clean logo image (PNG preferred).
  3. Brand profile — If the brand doesn't exist in the catalog, run brand-analyzer skill FIRST to generate one. Never submit with "No Brand" when a brand is known.
  4. Reference image — Search for an existing ad or visual with a style that matches what we're generating. Can be from previously generated images, the brand's campaigns, or found online. This dramatically improves output quality.

Auto-Preparation Workflow

When the user asks to generate an ad, follow this workflow:

1. User provides: product URL + brand name + objective

2. CHECK brand profile exists:
   → ls ~/clawd/ad-ready/configs/Brands/ | grep -i "{brand}"
   → If not found: run brand-analyzer skill first
   
3. DOWNLOAD product image:
   → Visit the product URL in browser or fetch the page
   → Find and download the main product image
   → Save to /tmp/ad-ready-product.jpg

4. DOWNLOAD brand logo:
   → Search "{brand name} logo PNG" or fetch from brand website
   → Download clean logo image
   → Save to /tmp/ad-ready-logo.png

5. FIND reference image:
   → Search for "{brand name} advertisement" or similar
   → Or use a previously generated ad that has the right style
   → Save to /tmp/ad-ready-reference.jpg

6. SELECT prompt profile based on objective:
   → Awareness: brand discovery, first impressions
   → Interest: engagement, curiosity
   → Consideration: comparison, features
   → Evaluation: deep dive, decision support
   → Conversion: purchase intent, CTAs (most common)
   → Retention: re-engagement
   → Loyalty: brand advocates
   → Advocacy: referral, community

7. RUN the generation with ALL inputs filled

Usage

Full command (recommended):

COMFY_DEPLOY_API_KEY="$KEY" uv run ~/.clawdbot/skills/ad-ready/scripts/generate.py \
  --product-url "https://shop.example.com/product" \
  --product-image "/tmp/product-photo.jpg" \
  --logo "/tmp/brand-logo.png" \
  --reference "/tmp/reference-ad.jpg" \
  --model "models-catalog/catalog/images/model_15.jpg" \
  --brand-profile "Nike" \
  --prompt-profile "Master_prompt_05_Conversion" \
  --aspect-ratio "4:5" \
  --output "ad-output.png"

Auto-fetch mode (downloads product image and logo automatically):

COMFY_DEPLOY_API_KEY="$KEY" uv run ~/.clawdbot/skills/ad-ready/scripts/generate.py \
  --product-url "https://shop.example.com/product" \
  --brand-profile "Nike" \
  --prompt-profile "Master_prompt_05_Conversion" \
  --auto-fetch \
  --output "ad-output.png"

The --auto-fetch flag will:

  • Download the main product image from the product URL
  • Search and download the brand logo
  • Both get uploaded to ComfyDeploy automatically

API Details

Endpoint: https://api.comfydeploy.com/api/run/deployment/queue Deployment ID: e37318e6-ef21-4aab-bc90-8fb29624cd15

ComfyDeploy Input Variables

These are the exact variable names the ComfyDeploy deployment expects:

VariableTypeDescription
product_urlstringProduct page URL to scrape
productoimage URLProduct image (uploaded to ComfyDeploy)
modelimage URLModel/talent face reference
referenciaimage URLStyle reference ad image
marcaimage URLBrand logo image
brand_profileenumBrand name from catalog
prompt_profileenumFunnel stage prompt
aspect_ratioenumOutput format

4-Phase Pipeline (How It Works Internally)

Phase 1: Product Scraping

  • Gemini Flash visits the product URL
  • Extracts: title, description, features, price, images
  • ⚠️ Image scraping is the most fragile part — always provide product images manually

Phase 2: Campaign Brief Generation (CRITICAL)

  • Uses Brand Identity JSON + Product Data → 10-point brief
  • Everything downstream depends on brief quality
  • Brief covers: strategic objective, central message, visual tone, product role, photographer, art direction, environment, textures, signature

Phase 3: Blueprint Generation

  • Master Prompt (per funnel stage) + Brief + Product JSON + Keyword Bank + Format
  • Gemini Flash generates complete Blueprint JSON
  • Covers: scene, production, graphic design, lighting, composition, materials, CTA

Phase 4: Image Generation

  • Nano Banana Pro (Imagen 3.0) generates the final image
  • Uses Blueprint JSON + all reference images (product, talent, logo, style ref)

Supporting Reference Nodes

  • pose_ref → enforce a specific pose (replicated exactly)
  • photo_style_ref → replicate photographic style (⚠️ can be too literal, being optimized)
  • location_ref → replicate location and color palette

Brand Profiles

Existing catalog (70+ brands):

ls ~/clawd/ad-ready/configs/Brands/*.json | sed 's/.*\///' | sed 's/\.json//'

Creating new brand profiles:

Use the brand-analyzer skill:

GEMINI_API_KEY="$KEY" uv run ~/.clawdbot/skills/brand-analyzer/scripts/analyze.py \
  --brand "Brand Name" --auto-save

This generates a full Brand Identity JSON and saves it to the catalog automatically.

Prompt Profiles (Funnel Stages)

ProfileStageBest For
Master_prompt_01_AwarenessAwarenessBrand discovery, first impressions
Master_prompt_02_InterestInterestEngagement, curiosity
Master_prompt_03_ConsiderationConsiderationComparison, features
Master_prompt_04_EvaluationEvaluationDeep dive, decision support
Master_prompt_05_ConversionConversionPurchase intent, CTAs
Master_prompt_06_RetentionRetentionRe-engagement, loyalty
Master_prompt_07_LoyaltyLoyaltyBrand advocates
Master_prompt_08_AdvocacyAdvocacyReferral, community

How to choose:

  • Most ads → Conversion (purchase intent)
  • New product launches → Awareness
  • Retargeting → Consideration or Evaluation
  • Existing customers → Retention or Loyalty

Aspect Ratios

RatioUse Case
4:5Default. Instagram feed, Facebook
9:16Stories, Reels, TikTok
1:1Square posts
16:9YouTube, landscape banners
5:4Alternative landscape

Model Catalog

Models for talent/face reference: ~/clawd/models-catalog/catalog/

Priority: User-provided model > Catalog selection > No model (product-only ad)

Known Limitations

  1. Product image scraping is fragile — always provide product images manually when possible
  2. photo_style_ref can be too literal — the style reference may be replicated too closely
  3. Some websites block scraping — Armani works well, others may return incorrect data
  4. Auto 4-Format is alpha — bugs and edge cases exist
  5. Gemini hallucinations — occasional issues in complex reasoning steps

Ad-Ready vs Morpheus

FeatureAd-ReadyMorpheus
InputProduct URL (auto-scrapes)Manual product image
Brand intelligence70+ brand profilesNone
Funnel targeting8 funnel stagesNone
Creative directionAuto-generated from briefPack-based (camera, lens, etc.)
Best forProduct advertising campaignsFashion/lifestyle editorial photography
Control levelHigh-level (objective-driven)Granular (every visual parameter)

Source Repository

  • GitHub: https://github.com/PauldeLavallaz/ads_SV
  • Local clone: ~/clawd/ad-ready/
  • Patreon docs: https://www.patreon.com/posts/from-product-to-149933468

API Key

Uses ComfyDeploy API key. Set via COMFY_DEPLOY_API_KEY environment variable.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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