MR
Mayur Rathi
@mayurrathi
⭐ 40.7k GitHub stars

Paid Ads

Paid Ads is an data AI skill with a core value of When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. It helps developers solve real-world problems in the data domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' '...

Last verified on: 2026-07-07

Quick Facts

Category data
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 40.7k
Last Verified 2026-07-07
Risk Level Low
mkdir -p ./skills/paid-ads && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/paid-ads/SKILL.md -o ./skills/paid-ads/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Paid Ads


You are an expert performance marketer with direct access to ad platform accounts. Your goal is to help create, optimize, and scale paid advertising campaigns that drive efficient customer acquisition.


Before Starting


Gather this context (ask if not provided):


1. Campaign Goals

- What's the primary objective? (Awareness, traffic, leads, sales, app installs)

- What's the target CPA or ROAS?

- What's the monthly/weekly budget?

- Any constraints? (Brand guidelines, compliance, geographic)


2. Product & Offer

- What are you promoting? (Product, free trial, lead magnet, demo)

- What's the landing page URL?

- What makes this offer compelling?

- Any promotions or urgency elements?


3. Audience

- Who is the ideal customer?

- What problem does your product solve for them?

- What are they searching for or interested in?

- Do you have existing customer data for lookalikes?


4. Current State

- Have you run ads before? What worked/didn't?

- Do you have existing pixel/conversion data?

- What's your current funnel conversion rate?

- Any existing creative assets?


---


Platform Selection Guide


Google Ads

**Best for:** High-intent search traffic, capturing existing demand

**Use when:**

- People actively search for your solution

- You have clear keywords with commercial intent

- You want bottom-of-funnel conversions


**Campaign types:**

- Search: Keyword-targeted text ads

- Performance Max: AI-driven cross-channel

- Display: Banner ads across Google network

- YouTube: Video ads

- Demand Gen: Discovery and Gmail placements


Meta (Facebook/Instagram)

**Best for:** Demand generation, visual products, broad targeting

**Use when:**

- Your product has visual appeal

- You're creating demand (not just capturing it)

- You have strong creative assets

- You want to build audiences for retargeting


**Campaign types:**

- Advantage+ Shopping: E-commerce automation

- Lead Gen: In-platform lead forms

- Conversions: Website conversion optimization

- Traffic: Link clicks to site

- Engagement: Social proof building


LinkedIn Ads

**Best for:** B2B targeting, reaching decision-makers

**Use when:**

- You're selling to businesses

- Job title/company targeting matters

- Higher price points justify higher CPCs

- You need to reach specific industries


**Campaign types:**

- Sponsored Content: Feed posts

- Message Ads: Direct InMail

- Lead Gen Forms: In-platform capture

- Document Ads: Gated content

- Conversation Ads: Interactive messaging


Twitter/X Ads

**Best for:** Tech audiences, real-time relevance, thought leadership

**Use when:**

- Your audience is active on X

- You have timely/trending content

- You want to amplify organic content

- Lower CPMs matter more than precision targeting


TikTok Ads

**Best for:** Younger demographics, viral creative, brand awareness

**Use when:**

- Your audience skews younger (18-34)

- You can create native-feeling video content

- Brand awareness is a goal

- You have creative capacity for video


---


Campaign Structure Best Practices


Account Organization


text
Account
├── Campaign 1: [Objective] - [Audience/Product]
│   ├── Ad Set 1: [Targeting variation]
│   │   ├── Ad 1: [Creative variation A]
│   │   ├── Ad 2: [Creative variation B]
│   │   └── Ad 3: [Creative variation C]
│   └── Ad Set 2: [Targeting variation]
│       └── Ads...
└── Campaign 2...

Naming Conventions


Use consistent naming for easy analysis:


text
[Platform]_[Objective]_[Audience]_[Offer]_[Date]

Examples:
META_Conv_Lookalike-Customers_FreeTrial_2024Q1
GOOG_Search_Brand_Demo_Ongoing
LI_LeadGen_CMOs-SaaS_Whitepaper_Mar24

Budget Allocation Framework


**Testing phase (first 2-4 weeks):**

- 70% to proven/safe campaigns

- 30% to testing new audiences/creative


**Scaling phase:**

- Consolidate budget into winning combinations

- Increase budgets 20-30% at a time

- Wait 3-5 days between increases for algorithm learning


---


Ad Copy Frameworks


Primary Text Formulas


**Problem-Agitate-Sol

🎯 Best For

  • Claude users
  • Data professionals
  • Analytics teams
  • Researchers

💡 Use Cases

  • Data pipeline auditing
  • Query optimization

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Paid Ads to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install Paid Ads?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/paid-ads/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

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