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ad-creative

When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform.

Install / Use

npx skills add coreyhaines31/marketingskills --skill ad-creative

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

100/100

Supported Platforms

Universal

Our assessment of ad-creative

ad-creative scores 100/100 on our quality scale, 7th of 585 AI & Machine Learning skills we index (top 2%).

Its SKILL.md is 22 KB long, well organised into 59 sections with 8 code examples: a thorough specification that gives an agent plenty to work with.

With 51,376 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 20 days ago, so ad-creative is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

ad-creative compared with similar skills

ad-creative has the highest quality score among these 4 similar skills, though 4 alternatives have been updated more recently.

SkillScoreStarsUpdatedFormat
ad-creative (this skill)by coreyhaines3110051.4k20d agoSKILL.md
claude-memby thedotmack10094.6ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10084.1k13d agoCLAUDE.md
headroomby headroomlabs-ai10073.7ktodayCLAUDE.md
CowAgentby zhayujie10047.1ktodayCLAUDE.md

Frequently asked questions

How do I install ad-creative?
Run npx skills add coreyhaines31/marketingskills --skill ad-creative. The install tabs above show the steps for each supported agent.
Which AI agents does ad-creative work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is ad-creative safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is ad-creative still maintained?
The repository was last updated 20 days ago, so ad-creative is actively maintained.

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,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'ad templates,' 'iMessage ad,' 'chat reveal 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,' 'UGC ad,' 'greenscreen ad,' 'TikTok/Reels ad format,' 'which ad format to make,' 'Meta ad format tier list,' or 'creative format taxonomy.' 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: 2.8.2

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.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, 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 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

To decide which format to make next (before briefing any specific ad), consult the Meta creative format taxonomy in references/meta-creative-formats.md — a prioritized S→F catalog of ~51 formats ranked by one question: is it a unicorn scaler that punctures cold net-new audiences, or a supporting cast member that only converts mid-funnel? Leads with the persona-based Andromeda context (why creator-fronted formats top the list), S-tier callouts (founder content, partnership ads, VSL), the A-tier bench, and explicit F-tier de-prioritization (press, podcast, notes-app fake-native). Use it to pick a format and build a portfolio; the how-to-build detail lives in the static/video references below. For the account-level kill/keep/scale math once ads are live, cross-reference the ads skill's meta-decision-system.md.

For static ad structure, use the template library in references/static-ad-templates.md — layout frameworks (Us vs. Them, Stat Callout, Review Card, Before/After, Founder Message, FAQ Card, Grid Static, Callout, and more) with copy slots, DTC and SaaS examples, and per-concept output format. Each template carries a tier (S–F) and funnel role (unicorn cold-scaler vs. mid-funnel supporting cast) so you reach for the right one first. Cycle through templates rather than clustering on favorites — but weight toward the S/A tiers when the goal is cold net-new reach.

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 creator/UGC short-form video — a tiered format library (reaction+demo hard cuts, "no yapping" split-screen tutorials, greenscreen reactions, plus Yapper, amateur investigation, David & Goliath, authority, VSL, green-screen commentary, conversation, duet/reaction, ASMR, and street-interview formats, each with a scale-vs-support tier and mechanics) and founder / organic-vlog structures (hero's journey, math, shiny-object, niche-guide, the three-capture shooting system, and the 0.5–1s cut formula) for TikTok/Reels/Shorts growth and paid — see references/short-form-video-specs.md. It also carries the vertical video production spec that applies to all 9:16 video this skill makes: the cross-platform safe-zone band (720×1200 text-safe area — the most-missed constraint), the classic TikTok caption recipe (white fill + black stroke, no pill), static-caption auto-si

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars51.4k
CategoryAI
Updated20d ago
Forks7.8k

Languages

JavaScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions