| name | ad-creative |
| description | When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' 'ad performance optimization,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'static ad concepts,' 'ad templates,' 'iMessage ad,' 'chat reveal ad,' 'fake DM ad,' 'ChatGPT ad,' 'Apple Notes ad,' 'AirDrop ad,' 'creative strategy,' 'creative roadmap,' 'creative retro,' 'hook writing,' 'creative review page,' 'present ad creative for approval,' 'motion video ad,' 'faceless video ad,' 'animated explainer ad,' 'motion collage ad,' or 'I need more ad variations.' Use this whenever someone needs to produce ad copy at scale or iterate on existing ads. For campaign strategy and targeting, see ads. For landing page copy, see copywriting. |
| metadata | {"version":"2.8.0"} |
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 a marketing/ or docs/marketing/ directory exists, run a tree command to find relevant files to the current task. Don't try to read every file, instead view README.md / overview-type documents first and then only read documents that are crucial to the hand.
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 four 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
Mode 3: Scaled Static Batches (Grounded)
For recurring static ad production at volume (e.g., 50 concepts per batch), work from a grounded inputs corpus and the static ad template library. Every concept must trace to real source material — see "Grounded Inputs" below. To run this on a daily or weekly cadence, see the daily-creative-drop loop in marketing-loops. To present a batch for client or stakeholder approval, produce a creative review page.
Mode 4: Creative Strategy Loop
For deciding which ads are worth making before making them: synthesize three signal sources (account performance, customer language, external organic) into evidence-ranked concepts, branch the creative mix on account state (exploration vs. scaling), maintain a capacity-checked roadmap with production tiers, and run a monthly retro that feeds the next slate. The full system lives in references/creative-roadmap.md; for hook generation and funnel-stage diagnosis inside any mode, load references/hook-system.md.
Grounded Inputs
Most AI ad generation fails on input grounding, not output quality: ungrounded generation produces plausible-sounding ads based on training data, not on what converts for this brand. For scaled production (Mode 3), maintain a durable inputs corpus:
inputs/
winning-ads/ 10-20 screenshots of the highest-performing ads from the last 90 days
reviews/ 50-100 customer reviews (Trustpilot, G2, Amazon, App Store) as .md/.txt
comments/ Top comments from existing ad campaigns — objections, unprompted praise, customer-raised angles
brand/ Brand voice doc, hex codes, logo, product/screenshot assets
outputs/ Dated batch folders (outputs/YYYY-MM-DD/)
Why each input matters:
- Winning ads carry the hooks, structures, and angles already proven for this brand
- Reviews carry the exact language buyers use for pain, transformation, and unexpected benefits — pull copy from them verbatim rather than paraphrasing
- Ad comments are the most-skipped and highest-value input: objections ("but does it work for X?") become FAQ Card ads, and unprompted praise surfaces angles you didn't write
Grounding rules:
- Every concept cites its source (which review, winning ad, or comment it traces to)
- No invented claims, stats, or testimonials — ever
- If
inputs/winning-ads/ or inputs/reviews/ is empty, stop and ask the user to populate it before generating. Do not generate ungrounded concepts as a fallback.
- Inputs decay: refresh
inputs/winning-ads/ as new ads scale; refresh inputs/reviews/ and inputs/comments/ monthly
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 static ad structure, use the 15-template library in references/static-ad-templates.md — layout frameworks (Us vs. Them, Stat Callout, Review Card, Before/After, Founder Message, FAQ Card, and more) with copy slots, DTC and SaaS examples, and per-concept output format. Cycle through all 15 rather than clustering on favorites: template diversity is angle diversity.
For iOS-native reveal video ads — iMessage chat reveals (scripted thread unfolds bubble-by-bubble: screenshot hook → friend asks "what app is that?" → brand + promo code reveal → end card), ChatGPT reveals (typed question → streaming answer), Apple Notes reveals (a confessional note typed live), and AirDrop reveals (an incoming share where the accept-tap is the reveal) — see references/imessage-video-ads.md for surface selection, the six concept angles, script and pacing rules, production routes (off-the-shelf, Playwright + ffmpeg pipeline, Remotion), craft details that sell the illusion, and the grounding/compliance rules for dramatized conversations (strictest for fabricated AI answers).
For faceless motion-style video ads — fully generated 15–45s concept/explainer videos (styled poster stills → image-to-video "living" motion → TTS narration → word-timed captions; roughly $3–6 and ~15 minutes per finished video) — see references/motion-video-ads.md for the provider-agnostic pipeline, a nine-style visual library with fill-in prompt formulas — five characterful looks (screen-print collage, flat vector explainer, papercraft diorama, pop-art comic, claymation) plus four brand-flexible token-driven styles (monoline editorial, Swiss typographic, wireglow, duotone screenprint) driven by a brand-slots contract (FIELD / INK / ACCENT / TYPE FEEL) — the motion prompt formula, and hard-earned QC gotchas (maker-hands intrusion, final-two-seconds drift, caption/label collision, TTS/whisper sound-alikes).
For image and video generation tools, 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:
- Generate hero creative with AI tools (exploratory, high-quality)
- Build Remotion templates based on winning patterns
- Batch produce variations with Remotion using data feeds
- 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"
Static Batch Output (Mode 3)
For scaled static batches, save to a dated folder with an index:
outputs/YYYY-MM-DD/
INDEX.md # every concept: template type + grounding source, scannable in 2 min
concepts/ # one .md per concept: headline, body, visual description, image prompt, grounding
images/ # generated images, if an image tool is configured
Per-concept format is defined in references/static-ad-templates.md. The human workflow this supports: open the folder, scan INDEX.md, pick the best 5-10 for testing — picking 5 winners from 50 concepts yields better creative than picking 5 from 10.
Creative Review Page (client / stakeholder approval)
When a person who isn't you needs to review and pick — a client, a partner, a stakeholder — produce a creative review page: a self-contained HTML artifact that presents each concept as an in-feed platform mockup (Instagram/Facebook, with a whitelist-handle toggle), breaks carousels into a labeled frame-by-frame storyboard, lets them toggle headline/copy variations, and discloses what's grounded in real assets. It's the visual upgrade to INDEX.md — a decision made off one link instead of by reading markdown. The template ships at assets/creative-review-template.html (one file, no build, hostable anywhere); populate its DATA object from your generated concepts. Full data model, grounding rules (the disclosure block is required), and delivery in references/creative-review-page.md.
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
- Generating without grounding — Ungrounded concepts read like every other ad in the feed; feed the skill winning ads, reviews, and comments first
- Skipping the comments input — Ad comments hold the objections and angles customers raise themselves; those usually convert best
- 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
node tools/clis/google-ads.js reports get --type ad_performance --date-range last_30_days
Related Skills
- ads: For campaign strategy, targeting, budgets, and optimization
- marketing-loops: For running static batch generation on a recurring cadence (the daily-creative-drop loop)
- customer-research: For mining reviews and comments when building the grounded inputs corpus
- copywriting: For landing page copy (where ad traffic lands)
- ab-testing: For structuring creative tests with statistical rigor
- marketing-psychology: For psychological principles behind high-performing creative
- copy-editing: For polishing ad copy before launch
