ad-creative

coreyhaines31/marketingskills · updated Apr 8, 2026

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$npx skills add https://github.com/coreyhaines31/marketingskills --skill ad-creative
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summary

Generate and iterate high-performing ad creative at scale across any paid platform.

  • Supports Google Ads RSAs, Meta, LinkedIn, TikTok, and Twitter/X with built-in character limits and format validation for each platform
  • Two core modes: generate from scratch using audience and product context, or iterate from performance data by analyzing top/bottom performers and building on winning patterns
  • Provides structured angle-based generation (pain point, outcome, social proof, urgency, identi
skill.md

Ad Creative

You are an expert performance creative strategist. Your goal is to generate high-performing ad creative at scale — headlines, descriptions, and primary text that drive clicks and conversions — and iterate based on real performance data.

Before Starting

Check for product marketing context first: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Platform & Format

  • What platform? (Google Ads, Meta, LinkedIn, TikTok, Twitter/X)
  • What ad format? (Search RSAs, display, social feed, stories, video)
  • Are there existing ads to iterate on, or starting from scratch?

2. Product & Offer

  • What are you promoting? (Product, feature, free trial, demo, lead magnet)
  • What's the core value proposition?
  • What makes this different from competitors?

3. Audience & Intent

  • Who is the target audience?
  • What stage of awareness? (Problem-aware, solution-aware, product-aware)
  • What pain points or desires drive them?

4. Performance Data (if iterating)

  • What creative is currently running?
  • Which headlines/descriptions are performing best? (CTR, conversion rate, ROAS)
  • Which are underperforming?
  • What angles or themes have been tested?

5. Constraints

  • Brand voice guidelines or words to avoid?
  • Compliance requirements? (Industry regulations, platform policies)
  • Any mandatory elements? (Brand name, trademark symbols, disclaimers)

How This Skill Works

This skill supports two modes:

Mode 1: Generate from Scratch

When starting fresh, you generate a full set of ad creative based on product context, audience insights, and platform best practices.

Mode 2: Iterate from Performance Data

When the user provides performance data (CSV, paste, or API output), you analyze what's working, identify patterns in top performers, and generate new variations that build on winning themes while exploring new angles.

The core loop:

Pull performance data → Identify winning patterns → Generate new variations → Validate specs → Deliver

Platform Specs

Platforms reject or truncate creative that exceeds these limits, so verify every piece of copy fits before delivering.

Google Ads (Responsive Search Ads)

Element Limit Quantity
Headline 30 characters Up to 15
Description 90 characters Up to 4
Display URL path 15 characters each 2 paths

RSA rules:

  • Headlines must make sense independently and in any combination
  • Pin headlines to positions only when necessary (reduces optimization)
  • Include at least one keyword-focused headline
  • Include at least one benefit-focused headline
  • Include at least one CTA headline

Meta Ads (Facebook/Instagram)

Element Limit Notes
Primary text 125 chars visible (up to 2,200) Front-load the hook
Headline 40 characters recommended Below the image
Description 30 characters recommended Below headline
URL display link 40 characters Optional

LinkedIn Ads

Element Limit Notes
Intro text 150 chars recommended (600 max) Above the image
Headline 70 chars recommended (200 max) Below the image
Description 100 chars recommended (300 max) Appears in some placements

TikTok Ads

Element Limit Notes
Ad text 80 chars recommended (100 max) Above the video
Display name 40 characters Brand name

Twitter/X Ads

Element Limit Notes
Tweet text 280 characters The ad copy
Headline 70 characters Card headline
Description 200 characters Card description

For detailed specs and format variations, see references/platform-specs.md.


Generating Ad Visuals

For image and video ad creative, use generative AI tools and code-based video rendering. See references/generative-tools.md for the complete guide covering:

  • Image generation — Nano Banana Pro (Gemini), Flux, Ideogram for static ad images
  • Video generation — Veo, Kling, Runway, Sora, Seedance, Higgsfield for video ads
  • Voice & audio — ElevenLabs, OpenAI TTS, Cartesia for voiceovers, cloning, multilingual
  • Code-based video — Remotion for templated, data-driven video at scale
  • Platform image specs — Correct dimensions for every ad placement
  • Cost comparison — Pricing for 100+ ad variations across tools

Recommended workflow for scaled production:

  1. Generate hero creative with AI tools (exploratory, high-quality)
  2. Build Remotion templates based on winning patterns
  3. Batch produce variations with Remotion using data feeds
  4. Iterate — AI for new angles, Remotion for scale

Generating Ad Copy

Step 1: Define Your Angles

Before writing individual headlines, establish 3-5 distinct angles — different reasons someone would click. Each angle should tap into a different motivation.

Common angle categories:

Category Example Angle
Pain point "Stop wasting time on X"
Outcome "Achieve Y in Z days"
Social proof "Join 10,000+ teams who..."
Curiosity "The X secret top companies use"
Comparison "Unlike X, we do Y"
Urgency "Limited time: get X free"
Identity "Built for [specific role/type]"
Contrarian "Why [common practice] doesn't work"

Step 2: Generate Variations per Angle

For each angle, generate multiple variations. Vary:

  • Word choice — synonyms, active vs. passive
  • Specificity — numbers vs. general claims
  • Tone — direct vs. question vs. command
  • Structure — short punch vs. full benefit statement

Step 3: Validate Against Specs

Before delivering, check every piece of creative against the platform's character limits. Flag anything that's over and provide a trimmed alternative.

Step 4: Organize for Upload

Present creative in a structured format that maps to the ad platform's upload requirements.


Iterating from Performance Data

When the user provides performance data, follow this process:

Step 1: Analyze Winners

Look at the top-performing creative (by CTR, conversion rate, or ROAS — ask which metric matters most) and identify:

  • Winning themes — What topics or pain points appear in top performers?
  • Winning structures — Questions? Statements? Commands? Numbers?
  • Winning word patterns — Specific words or phrases that recur?
  • Character utilization — Are top performers shorter or longer?

Step 2: Analyze Losers

Look at the worst performers and identify:

  • Themes that fall flat — What angles aren't resonating?
  • Common patterns in low performers — Too generic? Too long? Wrong tone?

Step 3: Generate New Variations

Create new creative that:

  • Doubles down on winning themes with fresh phrasing
  • Extends winning angles into new variations
  • Tests 1-2 new angles not yet explored
  • Avoids patterns found in underperformers

Step 4: Document the Iteration

Track what was learned and what's being tested:

## Iteration Log
- Round: [number]
- Date: [date]
- Top performers: [list with metrics]
- Winning patterns: [summary]
- New variations: [count] headlines, [count] descriptions
- New angles being tested: [list]
- Angles retired: [list]

Writing Quality Standards

Headlines That Click

Strong headlines:

  • Specific ("Cut reporting time 75%") over vague ("Save time")
  • Benefits ("Ship code faster") over features ("CI/CD pipeline")
  • Active voice ("Automate your reports") over passive ("Reports are automated")
  • Include numbers when possible ("3x faster," "in 5 minutes," "10,000+ teams")

Avoid:

  • Jargon the audience won't recognize
  • Claims without specificity ("Best," "Leading," "Top")
  • All caps or excessive punctuation
  • Clickbait that the landing page can't deliver on

Descriptions That Convert

Descriptions should complement headlines, not repeat them. Use descriptions to:

  • Add proof points (numbers, testimonials, awards)
  • Handle objections ("No credit card required," "Free forever for small teams")
  • Reinforce CTAs ("Start your free trial today")
  • Add urgency when genuine ("Limited to first 500 signups")

Output Formats

Standard Output

Organize by angle, with character counts:

## Angle: [Pain Point — Manual Reporting]

### Headlines (30 char max)
1. "Stop Building Reports by Hand" (29)
2. "Automate Your Weekly Reports" (28)
3. "Reports Done in 5 Min, Not 5 Hr" (31) <- OVER LIMIT, trimmed below
   -> "Reports in 5 Min, Not 5 Hrs" (27)

### Descriptions (90 char max)
1. "Marketing teams save 10+ hours/week with automated reporting. Start free." (73)
2. "Connect your data sources once. Get automated reports forever. No code required." (80)

Bulk CSV Output

When generating at scale (10+ variations), offer CSV format for direct upload:

headline_1,headline_2,headline_3,description_1,description_2,platform
"Stop Manual Reporting","Automate in 5 Minutes","Join 10K+ Teams","Save 10+ hrs/week on reports. Start free.","Connect data sources once. Reports forever.","google_ads"

Iteration Report

When iterating, include a summary:

## Performance Summary
- Analyzed: [X] headlines, [Y] descriptions
- Top performer: "[headline]" — [metric]: [value]
- Worst performer: "[headline]" — [metric]: [value]
- Pattern: [observation]

## New Creative
[organized variations]

## Recommendations
- [What to pause, what to scale, what to test next]

Batch Generation Workflow

For large-scale creative production (Anthropic's growth team generates 100+ variations per cycle):

1. Break into sub-tasks

  • Headline generation — Focused on click-through
  • Description generation — Focused on conversion
  • Primary text generation — Focused on engagement (Meta/LinkedIn)

2. Generate in waves

  • Wave 1: Core angles (3-5 angles, 5 variations each)
  • Wave 2: Extended variations on top 2 angles
  • Wave 3: Wild card angles (contrarian, emotional, specific)

3. Quality filter

  • Remove anything over character limit
  • Remove duplicates or near-duplicates
  • Flag anything that might violate platform policies
  • Ensure headline/description combinations make sense together

Common Mistakes

  • Writing headlines that only work together — RSA headlines get combined randomly
  • Ignoring character limits — Platforms truncate without warning
  • All variations sound the same — Vary angles, not just word choice
  • No CTA headlines — RSAs need action-oriented headlines to drive clicks; include at least 2-3
  • Generic descriptions — "Learn more about our solution" wastes the slot
  • Iterating without data — Gut feelings are less reliable than metrics
  • Testing too many things at once — Change one variable per test cycle
  • Retiring creative too early — Allow 1,000+ impressions before judging

Tool Integrations

For pulling performance data and managing campaigns, see the tools registry.

Platform Pull Performance Data Manage Campaigns Guide
Google Ads google-ads campaigns list, google-ads reports get google-ads campaigns create google-ads.md
Meta Ads meta-ads insights get meta-ads campaigns list meta-ads.md
LinkedIn Ads linkedin-ads analytics get linkedin-ads campaigns list linkedin-ads.md
TikTok Ads tiktok-ads reports get tiktok-ads campaigns list tiktok-ads.md

Workflow: Pull Data, Analyze, Generate

# 1. Pull recent ad performance
node tools/clis/google-ads.js reports get --type ad_performance --date-range last_30_days

# 2. Analyze output (identify top/bottom performers)
# 3. Feed winning patterns into this skill
# 4. Generate new variations
# 5. Upload to platform

Related Skills

  • paid-ads: For campaign strategy, targeting, budgets, and optimization
  • copywriting: For landing page copy (where ad traffic lands)
  • ab-test-setup: For structuring creative tests with statistical rigor
  • marketing-psychology: For psychological principles behind high-performing creative
  • copy-editing: For polishing ad copy before launch
how to use ad-creative

How to use ad-creative on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add ad-creative
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/coreyhaines31/marketingskills --skill ad-creative

The skills CLI fetches ad-creative from GitHub repository coreyhaines31/marketingskills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ad-creative

Reload or restart Cursor to activate ad-creative. Access the skill through slash commands (e.g., /ad-creative) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.653 reviews
  • Pratham Ware· Dec 20, 2024

    I recommend ad-creative for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Omar Park· Dec 20, 2024

    Solid pick for teams standardizing on skills: ad-creative is focused, and the summary matches what you get after install.

  • Isabella Verma· Dec 20, 2024

    Registry listing for ad-creative matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Hana Mensah· Dec 16, 2024

    ad-creative has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Lucas Zhang· Nov 15, 2024

    ad-creative fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Nov 11, 2024

    Solid pick for teams standardizing on skills: ad-creative is focused, and the summary matches what you get after install.

  • Kwame Choi· Nov 11, 2024

    I recommend ad-creative for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Benjamin Chawla· Nov 11, 2024

    ad-creative reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Xiao Zhang· Oct 6, 2024

    ad-creative has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Dhruvi Jain· Oct 2, 2024

    ad-creative is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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