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Ad Context Protocol (AdCP) Advertising

作者 edyyy62 · GitHub ↗ · v1.0.1
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在 OpenClaw 中安装
/install adcp-advertising
功能描述
Automate advertising campaigns with AI. Create ads, buy media, manage ad budgets, discover ad inventory, run display ads, video ads, CTV campaigns, and optimize ad performance. Perfect for marketing automation, programmatic advertising, media buying, ad management, campaign optimization, creative management, and performance tracking. Launch Facebook ads, Google ads, display advertising, video marketing, and multi-channel campaigns using natural language. Supports ad targeting, audience segmentation, ROI tracking, and automated bidding.
使用说明 (SKILL.md)

Ad Context Protocol (AdCP) Advertising Skill

Overview

Automate your advertising campaigns with AI. This skill enables OpenClaw agents to discover ad inventory, launch campaigns, manage creatives, and optimize performance across display, video, CTV, audio, and more - all through natural language commands.

No dashboards. No forms. No ad platform expertise required.

What You Can Do

  • 🎯 Launch campaigns in minutes - "Create a $10k display campaign targeting tech professionals in California"
  • 🔍 Discover ad inventory instantly - "Find premium video placements for luxury brands"
  • 🎨 Upload ads with ease - "Upload these banner images as creatives"
  • 📊 Track ROI in real-time - "Show me campaign performance and CTR by creative"
  • 🎛️ Auto-optimize spend - "Reallocate budget to top-performing packages"
  • 🌐 Target precisely - Demographics, behaviors, interests, locations, devices, times

Perfect For

Marketing teams running Facebook ads, Google ads, and multi-channel campaigns
Media buyers managing programmatic ad spend across publishers
Agencies automating client campaign management and reporting
E-commerce brands launching product ads and retargeting campaigns
Startups running lean marketing with AI-powered automation

Why Choose This Skill?

Skip the learning curve - No need to master complex ad platforms
Save time - Launch in 5 minutes vs. hours of manual setup
Spend smarter - AI automatically optimizes budgets to top performers
Scale faster - Manage unlimited campaigns through simple commands
Test risk-free - Public test agent included, no setup required

Official AdCP Repository: https://github.com/adcontextprotocol/adcp
Official AdCP Documentation: https://docs.adcontextprotocol.org
Complete Documentation Index: https://docs.adcontextprotocol.org/llms.txt

When to Use This Skill

Trigger this skill when users ask about:

Campaign Management

  • "Create a display ad campaign"
  • "Launch Facebook ads for my product"
  • "Set up a $5000 video advertising campaign"
  • "Pause my underperforming campaigns"

Ad Discovery & Media Buying

  • "Find advertising inventory for luxury brands"
  • "Show me CTV ad placements in major cities"
  • "What display ad options are available?"
  • "Buy media for a tech startup"

Creative Management

  • "Upload these banner images"
  • "Which creative is performing best?"
  • "Add video ads to my campaign"
  • "Manage my ad library"

Performance & Optimization

  • "How is my campaign performing?"
  • "Show me ROI by channel"
  • "Optimize my ad spend"
  • "Reallocate budget to top performers"
  • "Track impressions and click-through rates"

Targeting & Audiences

  • "Target professionals in California"
  • "Set up demographic targeting"
  • "Create a retargeting campaign"
  • "Target by device type and time of day"

Quick Start

Launch Your First Campaign (5 Minutes)

No setup required. Use the included test agent to try everything:

Step 1: Discover what's available

"Show me advertising capabilities"

Browse available channels, publishers, and formats.

Step 2: Find ad inventory

"Find display ads for a tech startup, budget $5000"

AI searches and shows matching products with pricing.

Step 3: Launch campaign

"Create campaign with Product prod_123, $5000 budget, targeting California tech professionals"

Campaign goes live instantly.

Step 4: Upload your ads

"Upload these banner images as creatives"

Drop files, get instant creative IDs.

Step 5: Monitor performance

"Show campaign metrics and ROI"

Real-time impressions, clicks, CTR, spend.

Real-World Usage Examples

Quick campaign launch:

User: "I need to run display ads for my SaaS product"
Agent: [Discovers products] "Found 5 display packages. Want details?"
User: "Create campaign with Product 1, $10k budget, target CTOs"
Agent: [Creates campaign] "Campaign live! ID: mb_abc123"

Performance optimization:

User: "How are my video ads performing?"
Agent: [Shows metrics] "Package A: 2.3% CTR, Package B: 0.8% CTR"
User: "Move $5k from B to A"
Agent: [Reallocates] "Budget updated. Package A now $15k"

Multi-channel campaign:

User: "Launch omnichannel campaign: display in CA, video in NYC, $50k total"
Agent: [Creates packages] "3 packages created across display and video"

How It Works

Natural Language Understanding

Speak naturally. The skill understands:

  • Budgets: "$5000", "five thousand dollars", "5k budget"
  • Locations: "California", "major US cities", "New York and LA"
  • Audiences: "tech professionals", "age 25-45", "high income"
  • Goals: "brand awareness", "drive conversions", "increase sales"

Progressive Workflow

1. Discovery Phase

"Find video advertising for luxury brands"

↓ Agent searches inventory ↓ Shows matched products with pricing ↓ Explains targeting and formats

2. Campaign Creation

"Create campaign with Product 1, $25k, target professionals"

↓ Agent creates media buy ↓ Sets up targeting overlay ↓ Returns campaign ID and status

3. Creative Management

"Upload my banner ads"

↓ Agent syncs creatives ↓ Assigns to campaign ↓ Returns creative IDs

4. Monitoring & Optimization

"Show performance"

↓ Agent fetches delivery data
↓ Shows metrics by package/creative
↓ Suggests optimizations

Core Operations

Create Campaign

const campaign = await testAgent.createMediaBuy({
  buyer_ref: 'campaign-2026-q1',
  brand_manifest: { url: 'https://acme.com' },
  packages: [{ product_id: 'premium_display', budget: 10000 }]
});

Upload Creatives

await testAgent.syncCreatives({
  creatives: [{ 
    buyer_ref: 'banner-300x250',
    url: 'https://cdn.acme.com/banner.jpg'
  }]
});

Monitor Performance

const delivery = await testAgent.getMediaBuyDelivery({
  media_buy_id: 'mb_abc123'
});
console.log(`CTR: ${delivery.totals.ctr}%, Spend: $${delivery.totals.spend}`);

See REFERENCE.md for complete API docs and EXAMPLES.md for detailed workflows.

Core Concepts

The 8 Media Buy Tasks

AdCP provides 8 standardized tasks for the complete advertising lifecycle. Learn more in the Media Buy Protocol documentation.

  1. get_adcp_capabilities - Discover agent features and portfolio (~1s)
  2. get_products - Find inventory using natural language (~60s)
  3. list_creative_formats - View creative specifications (~1s)
  4. create_media_buy - Launch campaigns (minutes-days, may require approval)
  5. update_media_buy - Modify campaigns (minutes-days)
  6. sync_creatives - Upload creative assets (minutes-days)
  7. list_creatives - Query creative library (~1s)
  8. get_media_buy_delivery - Track performance (~60s)

Complete task reference: https://docs.adcontextprotocol.org/docs/media-buy/task-reference/

Brand Manifest

Brand context can be provided two ways:

URL reference (recommended - agent fetches brand info):

{
  "brand_manifest": {
    "url": "https://brand.com"
  }
}

Inline manifest (full brand details):

{
  "brand_manifest": {
    "name": "Brand Name",
    "url": "https://brand.com",
    "tagline": "Brand tagline",
    "colors": { "primary": "#FF0000" },
    "logo": { "url": "https://cdn.brand.com/logo.png" }
  }
}

Pricing Models

Products support various pricing models:

  • CPM (Cost Per Mille/Thousand) - Fixed price per 1000 impressions
  • CPM-Auction - Bid-based pricing for impressions
  • CPCV (Cost Per Completed View) - Video completions
  • Flat-Fee - Fixed campaign cost
  • CPP (Cost Per Point) - Percentage of audience reached

For auction pricing, include bid_price in your package.

Asynchronous Operations

AdCP is not a real-time protocol. Operations may take:

  • ~1 second - Simple lookups (formats, creative lists)
  • ~60 seconds - AI/inference operations (product discovery)
  • Minutes to days - Operations requiring human approval (campaign creation)

Always check the status field in responses:

  • completed - Operation finished successfully
  • pending - Awaiting approval or processing
  • failed - Operation failed (check error details)

Targeting Capabilities

Apply targeting overlays to campaigns:

{
  targeting_overlay: {
    geo: {
      included: ['US-CA', 'US-NY'],  // DMA codes or regions
      excluded: ['US-TX']
    },
    demographics: {
      age_ranges: [{ min: 25, max: 44 }],
      genders: ['M', 'F']
    },
    behavioral: {
      interests: ['technology', 'gaming'],
      purchase_intent: ['consumer_electronics']
    },
    contextual: {
      keywords: ['innovation', 'design'],
      categories: ['IAB19'] // Technology & Computing
    }
  }
}

Common Workflows

Workflow 1: Campaign Discovery to Launch

// 1. Discover capabilities
const caps = await agent.getAdcpCapabilities({});

// 2. Find products
const products = await agent.getProducts({
  brief: 'Q1 2026 brand awareness campaign for tech startup',
  brand_manifest: { url: 'https://startup.com' },
  filters: { channels: ['display', 'video'] }
});

// 3. Check creative formats
const formats = await agent.listCreativeFormats({
  format_types: ['display', 'video']
});

// 4. Create campaign
const campaign = await agent.createMediaBuy({
  buyer_ref: 'q1-2026-awareness',
  brand_manifest: { url: 'https://startup.com' },
  packages: [
    {
      buyer_ref: 'pkg-001',
      product_id: products.products[0].product_id,
      pricing_option_id: 'cpm-standard',
      budget: 15000
    }
  ],
  start_time: { type: 'asap' },
  end_time: '2026-03-31T23:59:59Z'
});

// 5. Upload creatives
await agent.syncCreatives({
  creatives: [...], // Your creative assets
  assignments: {
    'creative_001': ['pkg-001']
  }
});

// 6. Monitor performance
const delivery = await agent.getMediaBuyDelivery({
  media_buy_id: campaign.media_buy_id
});

Workflow 2: Update Running Campaign

// Pause, adjust budget, and resume campaign
await agent.updateMediaBuy({
  media_buy_id: 'mb_abc123',
  updates: {
    status: 'paused',
    budget_change: 5000, // Add $5000
    end_time: '2026-04-30T23:59:59Z'
  }
});

// Resume after adjustments
await agent.updateMediaBuy({
  media_buy_id: 'mb_abc123',
  updates: { status: 'active' }
});

More workflow examples: See EXAMPLES.md for complete campaign scenarios including creative management, multi-channel campaigns, and optimization workflows.

Test Agent

For development and testing, use the public test agent:

Agent URL: https://test-agent.adcontextprotocol.org/mcp
Auth Token: 1v8tAhASaUYYp4odoQ1PnMpdqNaMiTrCRqYo9OJp6IQ

import { testAgent } from '@adcp/client/testing';

// No authentication needed for test agent
const result = await testAgent.getProducts({
  brief: 'Test campaign',
  brand_manifest: { url: 'https://example.com' }
});

Interactive testing available at: testing.adcontextprotocol.org

Error Handling

Common error patterns:

400 Bad Request - Invalid parameters:

{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "budget must be greater than 0",
    "field": "packages[0].budget"
  }
}

401 Unauthorized - Missing or invalid auth:

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "Invalid authentication token"
  }
}

404 Not Found - Invalid ID reference:

{
  "error": {
    "code": "NOT_FOUND",
    "message": "Product not found",
    "resource": "product_id: premium_video_30s"
  }
}

Always check for errors before processing responses:

if (result.error) {
  console.error(`Error: ${result.error.message}`);
  return;
}

Best Practices

1. Always Start with Capabilities

Call get_adcp_capabilities first to understand what the agent supports before making other requests.

2. Use Clear Buyer References

Use descriptive buyer_ref values for tracking:

  • Good: 'campaign-2026-q1-tech-launch'
  • Avoid: 'c1', 'test', 'abc'

3. Handle Async Operations

Check status field and implement polling for pending operations:

let status = 'pending';
while (status === 'pending') {
  await sleep(5000); // Wait 5 seconds
  const update = await agent.getMediaBuyDelivery({
    media_buy_id: campaign.media_buy_id
  });
  status = update.status;
}

4. Write Detailed Briefs

Better briefs lead to better product matches:

  • Good: 'Premium video inventory for luxury automotive brand targeting high-income professionals aged 35-54 in major metros. Focus on brand awareness with completion rates above 70%.'
  • Avoid: 'video ads', 'need advertising'

5. Validate Creative Formats

Always check list_creative_formats to ensure your creatives meet requirements before uploading.

6. Monitor Budget Pacing

Regularly check delivery metrics to ensure campaigns are pacing properly:

const delivery = await agent.getMediaBuyDelivery({
  media_buy_id: campaign.media_buy_id
});

const pacing = delivery.delivery.spend / delivery.delivery.budget;
console.log(`Budget pacing: ${(pacing * 100).toFixed(1)}%`);

Additional Resources

Official AdCP Documentation

This Skill's Documentation

Key Reminders

  1. AdCP is asynchronous - Operations may take minutes to days
  2. Human approval may be required - Check for pending status
  3. Start with capabilities - Always call get_adcp_capabilities first
  4. Brand context matters - Provide detailed brand manifests for better results
  5. Targeting is additive - Product targeting + your overlay = final targeting
  6. Creative formats are strict - Always validate against format specifications
  7. Monitor performance - Regular delivery checks ensure campaign success

Support

For help with AdCP:

安全使用建议
This package appears to be a documentation-driven AdCP client and is coherent with its stated purpose. Key things to consider before installing or enabling it for autonomous use: 1) The README includes an intentionally public test bearer token for a test agent — use that for development only. 2) To run real campaigns you must obtain production bearer tokens from sales agents; never paste production tokens into public repos or share them. 3) If you provide production credentials, the agent can create/modify media buys and thus spend real money — restrict credential scope, test thoroughly in the test environment, and consider limiting autonomous invocation or adding manual approval steps for spend-related actions. 4) The agent may fetch content from brand_manifest URLs you supply; only provide URLs you trust. 5) Verify the trustworthiness of the homepage/repository and confirm billing/onboarding procedures with any sales agent before switching to production. If you want, I can highlight specific places in the docs where tokens, endpoints, or remote fetches are used so you can audit them more closely.
功能分析
Type: OpenClaw Skill Name: adcp-advertising Version: 1.0.1 The skill bundle provides extensive documentation and examples for integrating with the Ad Context Protocol (AdCP) to manage advertising campaigns. All content, including code snippets and instructions in SKILL.md and other markdown files, is clearly aligned with the stated purpose of advertising automation. The public test agent URL and authentication token (e.g., `https://test-agent.adcontextprotocol.org/mcp` and `1v8tAhASaUYYp4odoQ1PnMpdqNaMiTrCRqYo9OJp6IQ`) are explicitly documented as 'intentionally public' for testing purposes in SKILL.md and README.md, and advice is given to store production credentials securely. There is no evidence of intentional harmful behavior, data exfiltration, persistence, or prompt injection attempts against the OpenClaw agent.
能力评估
Purpose & Capability
The name/description (programmatic ad buying, creative management, campaign optimization) matches the included SKILL.md and documentation files. The skill describes discovering inventory, creating media buys, uploading creatives, and tracking performance — all of which are supported by the provided API-like examples. The claim of launching Facebook/Google ads is implemented via the AdCP agent layer (agent endpoints and sales-agent credentials) rather than direct Facebook/Google credentials, which is plausible for a protocol intermediary.
Instruction Scope
SKILL.md and other docs instruct the agent to call AdCP agent endpoints, upload creative assets (URLs or file drops), fetch brand_manifest URLs for brand context, and use a test agent for development. There are no instructions to read unrelated local files or harvest system secrets. Note: the docs instruct that authenticated operations require bearer tokens and recommend storing them in env/secret managers; the agent may fetch remote URLs (brand_manifest.url), which could cause it to retrieve external content as part of normal operation.
Install Mechanism
This is an instruction-only skill with no install spec and no code files to execute; that is the lowest-risk install model and consistent with the documentation-oriented package.
Credentials
The skill declares no required environment variables, which is consistent for an instruction-only skill. However, the README documents that authenticated (production) operations require bearer tokens and includes a deliberately public test token for the test agent. The skill itself does not request unrelated credentials. Be aware that providing production bearer tokens enables real ad buys and billing actions.
Persistence & Privilege
always:false and default agent-invocation behavior are appropriate. The skill does not request persistent installation privileges or configuration changes to other skills. One operational risk to note: if you supply production credentials, an autonomously-invoking agent could create or modify media buys (financial effect), so consider agent autonomy settings and credential scope.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install adcp-advertising
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /adcp-advertising 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
- Simplified metadata structure: added display name, author, license, homepage, repository, category, and expanded keywords. - Dramatically streamlined and modernized the documentation for faster onboarding, practical usage examples, and clear real-world use cases. - Improved natural language guidance, making it easier to understand how to launch, optimize, and track ad campaigns without technical knowledge. - Emphasized key use cases, including programmatic buying, campaign management, creative upload, and performance monitoring. - Removed legacy files (e.g., package.json) and replaced verbose, technical details with concise, action-oriented instructions. - The skill now targets a wider, less technical audience with direct, workflow-focused guidance for advertising automation.
v1.0.0
# Version 1.0.0 - Initial Release **Release Date**: January 31, 2026 **Status**: Initial Public Release ## What This Repository Does The **Ad Context Protocol (AdCP) Advertising** skill enables OpenClaw AI agents to autonomously discover, create, manage, and optimize advertising campaigns using natural language. Built on the Ad Context Protocol (AdCP) open standard, this skill provides a comprehensive interface for programmatic advertising automation across multiple channels. ### Core Purpose This skill bridges the gap between AI agents and the advertising ecosystem, allowing agents to: - Discover advertising inventory through natural language queries - Create and manage multi-channel campaigns - Upload and organize creative assets - Monitor real-time campaign performance - Optimize campaigns based on data and feedback All through conversational commands, without requiring manual platform navigation or technical advertising expertise. ## What We Achieved in v1.0.0 ### Complete AdCP Implementation **8 Core Tasks Fully Implemented:** 1. `get_adcp_capabilities` - Discover agent capabilities and portfolio 2. `get_products` - AI-powered product discovery with natural language 3. `create_media_buy` - Create campaigns with targeting and budgets 4. `update_media_buy` - Modify existing campaigns 5. `sync_creatives` - Upload and manage creative assets 6. `list_creatives` - Browse creative library 7. `get_media_buy_delivery` - Monitor campaign performance 8. `provide_performance_feedback` - Submit optimization signals ### Comprehensive Documentation **5,612 lines of professional documentation across 11 files:** - **SKILL.md** (462 lines) - Quick start and core concepts, under 500-line requirement - **README.md** (383 lines) - Enhanced with authentication guide and use cases - **REFERENCE.md** (1,306 lines) - Complete API reference for all 8 tasks - **EXAMPLES.md** (1,030 lines) - Real-world campaign examples across all channels - **PROTOCOLS.md** (418 lines) - MCP vs A2A protocol comparison and integration - **TARGETING.md** (685 lines) - Advanced targeting strategies - **CREATIVE.md** (704 lines) - Creative asset management guide - **QUICKREF.md** (273 lines) - Quick reference card - **CLAWHUB.md** (249 lines) - Publishing guide - **package.json** (80 lines) - Complete metadata and configuration - **LICENSE** - MIT open source license ### Multi-Channel Support **6 Advertising Channels Fully Supported:** - Display advertising (banner ads, rich media, HTML5) - Video advertising (pre-roll, mid-roll, outstream) - Connected TV (CTV) - Audio advertising (streaming audio, podcasts) - Native advertising (in-feed, content-style) - Digital Out-of-Home (DOOH) ### Authentication & Testing **Comprehensive Authentication Documentation:** - Clear explanation of public vs authenticated operations - Tiered authentication model documentation - Bearer token authentication with JWT support - Production credential acquisition guide - Configuration examples for test and production environments **Public Test Agent Included:** - URL: `https://test-agent.adcontextprotocol.org/mcp` - Public test token: `1v8tAhASaUYYp4odoQ1PnMpdqNaMiTrCRqYo9OJp6IQ` - Interactive testing portal: https://testing.adcontextprotocol.org - Zero-setup testing for users ### User Experience Features **"Your First Ad Campaign (5 Minutes)" Tutorial:** - Step-by-step guide from zero to first campaign - Uses public test agent (no authentication setup needed) - Natural language examples throughout **Target Audience Documentation:** - Marketing Teams - Media Buyers - Agencies - Developers **Real-World Use Cases:** - Launch New Product Campaign - Optimize Existing Campaign - Multi-Channel Strategy ### Protocol Support **Dual Protocol Implementation:** - MCP (Model Context Protocol) - Full support - A2A (Agent-to-Agent) - Full support - Comprehensive protocol comparison guide - Integration examples for both protocols ### Production-Ready Features **Quality Assurance:** - Error handling patterns for all tasks - Async operation handling with status checks - Input validation examples - Best practices throughout documentation - Troubleshooting guides **Progressive Disclosure Architecture:** - Core concepts in SKILL.md (quick to load) - Detailed APIs in REFERENCE.md - Advanced strategies in specialized guides - Fast lookups in QUICKREF.md ### Community-Ready **Open Source:** - MIT License for maximum compatibility - No personal information or proprietary code - Community-based authorship - Generic, reusable patterns **Official AdCP Integration:** - Official repository linked: https://github.com/adcontextprotocol/adcp - Clear distinction between skill and protocol - Upstream field in package.json - Links to official documentation throughout **ClawHub Submission Ready:** - All required files present and validated - Under 500-line SKILL.md requirement met - Proper frontmatter with trigger terms - Third-person description - Test agent credentials included ## Technical Achievements ### Code Quality - No checkmarks or decorative elements in user-facing documentation - Consistent formatting across all files - Professional tone and structure - Clear code examples with comments - Real working patterns (not pseudocode) ### Documentation Quality - Progressive disclosure from basic to advanced - Cross-references between related topics - Consistent terminology throughout - Search-optimized with relevant keywords - AI agent-friendly structure ### Metadata - Complete package.json with all required fields - Proper OpenClaw compatibility declarations - Test agent configuration included - Repository and bug tracker URLs - Upstream protocol attribution ## Release Statistics **Files Created:** 11 markdown files + package.json + LICENSE **Total Lines:** 5,612 lines of documentation **Code Examples:** 1,030 lines of real-world examples **Tasks Documented:** 8 complete AdCP tasks **Channels Supported:** 6 advertising channels **Protocols:** 2 (MCP and A2A) ## What's Next This initial release provides a complete, production-ready skill for advertising automation. Future enhancements may include: - Webhook integration examples - Advanced optimization algorithms - Pre-built campaign templates - Reporting dashboard examples - Analytics platform integrations - Budget forecasting and predictive pacing ## Installation ```bash # Via ClawHub (when published) openclaw skills install adcp-advertising # Manual Installation cd ~/.openclaw/workspace/skills/ git clone https://github.com/edyyy62/openclaw-adcp adcp-advertising openclaw gateway restart ``` ## Quick Start After installation: ``` "What advertising capabilities do I have access to?" "Find video advertising inventory for a tech company" "Create a display campaign targeting professionals in New York" ``` ## Links - **Repository**: https://github.com/edyyy62/openclaw-adcp - **Official AdCP**: https://github.com/adcontextprotocol/adcp - **AdCP Documentation**: https://docs.adcontextprotocol.org - **Test Environment**: https://testing.adcontextprotocol.org --- **v1.0.0** marks the successful completion of a comprehensive, production-ready skill that brings professional advertising automation to OpenClaw agents. The skill is ready for ClawHub submission and community distribution.
元数据
Slug adcp-advertising
版本 1.0.1
许可证
累计安装 1
当前安装数 1
历史版本数 2
常见问题

Ad Context Protocol (AdCP) Advertising 是什么?

Automate advertising campaigns with AI. Create ads, buy media, manage ad budgets, discover ad inventory, run display ads, video ads, CTV campaigns, and optimize ad performance. Perfect for marketing automation, programmatic advertising, media buying, ad management, campaign optimization, creative management, and performance tracking. Launch Facebook ads, Google ads, display advertising, video marketing, and multi-channel campaigns using natural language. Supports ad targeting, audience segmentation, ROI tracking, and automated bidding. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 3371 次。

如何安装 Ad Context Protocol (AdCP) Advertising?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install adcp-advertising」即可一键安装,无需额外配置。

Ad Context Protocol (AdCP) Advertising 是免费的吗?

是的,Ad Context Protocol (AdCP) Advertising 完全免费(开源免费),可自由下载、安装和使用。

Ad Context Protocol (AdCP) Advertising 支持哪些平台?

Ad Context Protocol (AdCP) Advertising 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ad Context Protocol (AdCP) Advertising?

由 edyyy62(@edyyy62)开发并维护,当前版本 v1.0.1。

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