Úsalo para generar, iterar o escalar creatividad publicitaria —titulares, descripciones, texto primario o variaciones completas— en cualquier plataforma de pago.
en todo el repo
0–100, la ruta de este skill
último commit aquí
últimos 90 días
254 tok en reposo
158 KB
Funciona con cualquier agente que lea SKILL.md
npx -y skills add coreyhaines31/marketingskills --skill ad-creative --agent claude-codeSe instala solo en este repositorio.
Di cualquiera de estas frases y el agente debería cargar este skill.
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.
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):
This skill supports four modes:
When starting fresh, you generate a full set of ad creative based on product context, audience insights, and platform best practices.
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
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.
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.
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:
Grounding rules:
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/winning-ads/ as new ads scale; refresh inputs/reviews/ and inputs/comments/ monthlyPlatforms reject or truncate creative that exceeds these limits, so verify every piece of copy fits before delivering.
| 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:
| 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 |
| 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 |
| Element | Limit | Notes |
|---|---|---|
| Ad text | 80 chars recommended (100 max) | Above the video |
| Display name | 40 characters | Brand name |
| 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.
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:
Recommended workflow for scaled production:
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" |
For each angle, generate multiple variations. Vary:
Before delivering, check every piece of creative against the platform's character limits. Flag anything that's over and provide a trimmed alternative.
Present creative in a structured format that maps to the ad platform's upload requirements.
When the user provides performance data, follow this process:
Look at the top-performing creative (by CTR, conversion rate, or ROAS — ask which metric matters most) and identify:
Look at the worst performers and identify:
Create new creative that:
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]
Strong headlines:
Avoid:
Descriptions should complement headlines, not repeat them. Use descriptions to:
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)
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"
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.
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.
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]
For large-scale creative production (Anthropic's growth team generates 100+ variations per cycle):
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 |
# 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
Reproducido de coreyhaines31/marketingskills bajo licencia MIT. Leer esta página en markdown.
11 archivos en el paquete. Solo se lee SKILL.md al activarse — las referencias se cargan si el skill decide que las necesita.
Para producción escalada (Modo 3) se necesita un corpus de inputs verificado (winning-ads, reviews, comments) en inputs/, y para integraciones de datos se requieren los CLIs de la registry de herramientas (google-ads, meta-ads, linkedin-ads, tiktok-ads).
Necesita en el PATH:node
Este repo incluye 49 skills. Si instalas uno, normalmente ya tienes los demás.
Para campañas de publicidad pagada en Google Ads, Meta, LinkedIn, Twitter/X u otras plataformas: estrategia, targeting, bidding y optimización de anuncios.
Para decisiones de pricing, packaging o monetización: tiers, freemium, prueba gratuita, aumentos de precio, valor percibido y auditorías de páginas de pricing para humanos y agentes de IA.
Ayuda a crear, programar y optimizar contenido de redes sociales para LinkedIn, Twitter/X, Instagram, TikTok o Facebook, y a hacer escucha social y triage de engagement.
Para cuando el usuario quiere saber qué marketing impulsa realmente conversiones e ingresos, elegir un modelo de atribución o reconciliar cifras contradictorias entre herramientas.
Para montar un flujo de marketing recurrente y autoejecutable que un agente corre en una cadencia, en vez de una tarea puntual; orquesta otras skills de marketing como un loop siempre activo.
Para cuando el usuario quiere realizar, analizar o sintetizar investigación de clientes: entrevistas, encuestas, tickets, reseñas o mining en comunidades online como Reddit y G2.
Úsalo cuando el usuario quiera planear un lanzamiento de producto, anuncio de feature o estrategia de release, incluyendo Product Hunt, beta launch, early access o waitlist.
Extrae automáticamente el sitio web oficial y los perfiles de redes sociales de una empresa, ya sea a partir de su nombre o de la URL de su sitio web.
Auditoría de sobre-ingeniería en todo el repo, no solo un diff: lista rankeada de qué borrar, simplificar o reemplazar por stdlib/nativo. Reporte de una sola vez, no aplica los cambios.
