Merge pull request #59 from coreyhaines31/feature/ai-seo-skill
Add ai-seo skill for AI search optimization
This commit is contained in:
Corey Haines
GitHub
commit
8f8ae292ea
13 changed files with 1782 additions and 3 deletions
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@ -12,11 +12,13 @@
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"plugins": [
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{
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"name": "marketing-skills",
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"description": "26 marketing skills for technical marketers and founders: CRO, copywriting, cold email, SEO, paid ads, pricing strategy, referral programs, and more",
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"description": "28 marketing skills for technical marketers and founders: CRO, copywriting, cold email, SEO, AI SEO, paid ads, ad creative, pricing strategy, referral programs, and more",
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"source": "./",
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"strict": false,
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"skills": [
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"./skills/ab-test-setup",
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"./skills/ad-creative",
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"./skills/ai-seo",
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"./skills/analytics-tracking",
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"./skills/cold-email",
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"./skills/competitor-alternatives",
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@ -18,6 +18,8 @@ Skills are markdown files that give AI agents specialized knowledge and workflow
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| Skill | Description |
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|-------|-------------|
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| [ab-test-setup](skills/ab-test-setup/) | When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B... |
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| [ad-creative](skills/ad-creative/) | When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad... |
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| [ai-seo](skills/ai-seo/) | When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers... |
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| [analytics-tracking](skills/analytics-tracking/) | When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions... |
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| [cold-email](skills/cold-email/) | Write B2B cold emails and follow-up sequences that get replies. Use when the user wants to write cold outreach emails,... |
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| [competitor-alternatives](skills/competitor-alternatives/) | When the user wants to create competitor comparison or alternative pages for SEO and sales enablement. Also use when... |
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@ -161,12 +163,14 @@ You can also invoke skills directly:
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### SEO & Discovery
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- `seo-audit` - Technical and on-page SEO
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- `ai-seo` - AI search optimization (AEO, GEO, LLMO)
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- `programmatic-seo` - Scaled page generation
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- `competitor-alternatives` - Comparison and alternative pages
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- `schema-markup` - Structured data
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### Paid & Distribution
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- `paid-ads` - Google, Meta, LinkedIn ad campaigns
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- `ad-creative` - Bulk ad creative generation and iteration
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- `social-content` - Social media scheduling and strategy
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### Measurement & Testing
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@ -5,6 +5,8 @@ Current versions of all skills. Agents can compare against local versions to che
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| Skill | Version | Last Updated |
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|-------|---------|--------------|
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| ab-test-setup | 1.0.0 | 2026-01-27 |
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| ad-creative | 1.0.0 | 2026-02-17 |
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| ai-seo | 1.0.0 | 2026-02-18 |
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| analytics-tracking | 1.0.0 | 2026-01-27 |
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| cold-email | 1.0.0 | 2026-02-14 |
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| competitor-alternatives | 1.0.0 | 2026-01-27 |
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@ -33,7 +35,12 @@ Current versions of all skills. Agents can compare against local versions to che
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## Recent Changes
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### 2026-02-18
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- Added `ai-seo` skill for AI search optimization (AEO, GEO, LLMO, AI Overviews)
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- Moved AEO/GEO content patterns from `seo-audit` references to `ai-seo` skill
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### 2026-02-17
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- Added `ad-creative` skill for bulk ad creative generation and performance-based iteration
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- Added 51 zero-dependency CLI tools for marketing platforms (`tools/clis/`)
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- Added 31 new integration guides (`tools/integrations/`)
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- Added 4 email outreach CLIs: hunter, snov, lemlist, instantly
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362
skills/ad-creative/SKILL.md
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362
skills/ad-creative/SKILL.md
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---
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name: ad-creative
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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,' or 'ad performance optimization.' This skill covers generating ad creative at scale, iterating based on performance data, and enforcing platform character limits. For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting."
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metadata:
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version: 1.0.0
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---
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# Ad Creative
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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.
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## Before Starting
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**Check for product marketing context first:**
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If `.claude/product-marketing-context.md` exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
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Gather this context (ask if not provided):
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### 1. Platform & Format
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- What platform? (Google Ads, Meta, LinkedIn, TikTok, Twitter/X)
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- What ad format? (Search RSAs, display, social feed, stories, video)
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- Are there existing ads to iterate on, or starting from scratch?
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### 2. Product & Offer
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- What are you promoting? (Product, feature, free trial, demo, lead magnet)
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- What's the core value proposition?
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- What makes this different from competitors?
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### 3. Audience & Intent
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- Who is the target audience?
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- What stage of awareness? (Problem-aware, solution-aware, product-aware)
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- What pain points or desires drive them?
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### 4. Performance Data (if iterating)
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- What creative is currently running?
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- Which headlines/descriptions are performing best? (CTR, conversion rate, ROAS)
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- Which are underperforming?
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- What angles or themes have been tested?
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### 5. Constraints
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- Brand voice guidelines or words to avoid?
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- Compliance requirements? (Industry regulations, platform policies)
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- Any mandatory elements? (Brand name, trademark symbols, disclaimers)
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---
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## How This Skill Works
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This skill supports two modes:
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### Mode 1: Generate from Scratch
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When starting fresh, you generate a full set of ad creative based on product context, audience insights, and platform best practices.
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### Mode 2: Iterate from Performance Data
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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.
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The core loop:
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```
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Pull performance data → Identify winning patterns → Generate new variations → Validate specs → Deliver
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```
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---
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## Platform Specs
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**Always enforce these limits.** Never deliver creative that exceeds platform character limits.
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### Google Ads (Responsive Search Ads)
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| Element | Limit | Quantity |
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|---------|-------|----------|
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| Headline | 30 characters | Up to 15 |
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| Description | 90 characters | Up to 4 |
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| Display URL path | 15 characters each | 2 paths |
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**RSA rules:**
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- Headlines must make sense independently and in any combination
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- Pin headlines to positions only when necessary (reduces optimization)
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- Include at least one keyword-focused headline
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- Include at least one benefit-focused headline
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- Include at least one CTA headline
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### Meta Ads (Facebook/Instagram)
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| Element | Limit | Notes |
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|---------|-------|-------|
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| Primary text | 125 chars visible (up to 2,200) | Front-load the hook |
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| Headline | 40 characters recommended | Below the image |
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| Description | 30 characters recommended | Below headline |
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| URL display link | 40 characters | Optional |
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### LinkedIn Ads
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| Element | Limit | Notes |
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|---------|-------|-------|
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| Intro text | 150 chars recommended (600 max) | Above the image |
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| Headline | 70 chars recommended (200 max) | Below the image |
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| Description | 100 chars recommended (300 max) | Appears in some placements |
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### TikTok Ads
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| Element | Limit | Notes |
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|---------|-------|-------|
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| Ad text | 80 chars recommended (100 max) | Above the video |
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| Display name | 40 characters | Brand name |
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### Twitter/X Ads
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| Element | Limit | Notes |
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|---------|-------|-------|
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| Tweet text | 280 characters | The ad copy |
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| Headline | 70 characters | Card headline |
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| Description | 200 characters | Card description |
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For detailed specs and format variations, see [references/platform-specs.md](references/platform-specs.md).
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---
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## Generating Ad Visuals
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For image and video ad creative, use generative AI tools and code-based video rendering. See [references/generative-tools.md](references/generative-tools.md) for the complete guide covering:
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- **Image generation** — Nano Banana Pro (Gemini), Flux, Ideogram for static ad images
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- **Video generation** — Veo, Kling, Runway, Sora, Seedance, Higgsfield for video ads
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- **Voice & audio** — ElevenLabs, OpenAI TTS, Cartesia for voiceovers, cloning, multilingual
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- **Code-based video** — Remotion for templated, data-driven video at scale
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- **Platform image specs** — Correct dimensions for every ad placement
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- **Cost comparison** — Pricing for 100+ ad variations across tools
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**Recommended workflow for scaled production:**
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1. Generate hero creative with AI tools (exploratory, high-quality)
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2. Build Remotion templates based on winning patterns
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3. Batch produce variations with Remotion using data feeds
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4. Iterate — AI for new angles, Remotion for scale
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---
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## Generating Ad Copy
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### Step 1: Define Your Angles
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Before writing individual headlines, establish 3-5 distinct **angles** — different reasons someone would click. Each angle should tap into a different motivation.
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**Common angle categories:**
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| Category | Example Angle |
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|----------|---------------|
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| Pain point | "Stop wasting time on X" |
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| Outcome | "Achieve Y in Z days" |
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| Social proof | "Join 10,000+ teams who..." |
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| Curiosity | "The X secret top companies use" |
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| Comparison | "Unlike X, we do Y" |
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| Urgency | "Limited time: get X free" |
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| Identity | "Built for [specific role/type]" |
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| Contrarian | "Why [common practice] doesn't work" |
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### Step 2: Generate Variations per Angle
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For each angle, generate multiple variations. Vary:
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- **Word choice** — synonyms, active vs. passive
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- **Specificity** — numbers vs. general claims
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- **Tone** — direct vs. question vs. command
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- **Structure** — short punch vs. full benefit statement
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### Step 3: Validate Against Specs
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Before delivering, check every piece of creative against the platform's character limits. Flag anything that's over and provide a trimmed alternative.
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### Step 4: Organize for Upload
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Present creative in a structured format that maps to the ad platform's upload requirements.
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---
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## Iterating from Performance Data
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When the user provides performance data, follow this process:
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### Step 1: Analyze Winners
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Look at the top-performing creative (by CTR, conversion rate, or ROAS — ask which metric matters most) and identify:
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- **Winning themes** — What topics or pain points appear in top performers?
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- **Winning structures** — Questions? Statements? Commands? Numbers?
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- **Winning word patterns** — Specific words or phrases that recur?
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- **Character utilization** — Are top performers shorter or longer?
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### Step 2: Analyze Losers
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Look at the worst performers and identify:
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- **Themes that fall flat** — What angles aren't resonating?
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- **Common patterns in low performers** — Too generic? Too long? Wrong tone?
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### Step 3: Generate New Variations
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Create new creative that:
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- **Doubles down** on winning themes with fresh phrasing
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- **Extends** winning angles into new variations
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- **Tests** 1-2 new angles not yet explored
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- **Avoids** patterns found in underperformers
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### Step 4: Document the Iteration
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Track what was learned and what's being tested:
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```
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## Iteration Log
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- Round: [number]
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- Date: [date]
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- Top performers: [list with metrics]
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- Winning patterns: [summary]
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- New variations: [count] headlines, [count] descriptions
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- New angles being tested: [list]
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- Angles retired: [list]
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```
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---
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## Writing Quality Standards
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### Headlines That Click
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**Strong headlines:**
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- Specific ("Cut reporting time 75%") over vague ("Save time")
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- Benefits ("Ship code faster") over features ("CI/CD pipeline")
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- Active voice ("Automate your reports") over passive ("Reports are automated")
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- Include numbers when possible ("3x faster," "in 5 minutes," "10,000+ teams")
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**Avoid:**
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- Jargon the audience won't recognize
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- Claims without specificity ("Best," "Leading," "Top")
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- All caps or excessive punctuation
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- Clickbait that the landing page can't deliver on
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### Descriptions That Convert
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Descriptions should complement headlines, not repeat them. Use descriptions to:
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- Add proof points (numbers, testimonials, awards)
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- Handle objections ("No credit card required," "Free forever for small teams")
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- Reinforce CTAs ("Start your free trial today")
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- Add urgency when genuine ("Limited to first 500 signups")
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---
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## Output Formats
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### Standard Output
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Organize by angle, with character counts:
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```
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## Angle: [Pain Point — Manual Reporting]
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### Headlines (30 char max)
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1. "Stop Building Reports by Hand" (29)
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2. "Automate Your Weekly Reports" (28)
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3. "Reports Done in 5 Min, Not 5 Hr" (31) <- OVER LIMIT, trimmed below
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-> "Reports in 5 Min, Not 5 Hrs" (27)
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### Descriptions (90 char max)
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1. "Marketing teams save 10+ hours/week with automated reporting. Start free." (73)
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2. "Connect your data sources once. Get automated reports forever. No code required." (80)
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```
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### Bulk CSV Output
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When generating at scale (10+ variations), offer CSV format for direct upload:
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```csv
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headline_1,headline_2,headline_3,description_1,description_2,platform
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"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"
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```
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### Iteration Report
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When iterating, include a summary:
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```
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## Performance Summary
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- Analyzed: [X] headlines, [Y] descriptions
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- Top performer: "[headline]" — [metric]: [value]
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- Worst performer: "[headline]" — [metric]: [value]
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- Pattern: [observation]
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## New Creative
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[organized variations]
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## Recommendations
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- [What to pause, what to scale, what to test next]
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```
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---
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## Batch Generation Workflow
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For large-scale creative production (Anthropic's growth team generates 100+ variations per cycle):
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### 1. Break into sub-tasks
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- **Headline generation** — Focused on click-through
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- **Description generation** — Focused on conversion
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- **Primary text generation** — Focused on engagement (Meta/LinkedIn)
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### 2. Generate in waves
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- Wave 1: Core angles (3-5 angles, 5 variations each)
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- Wave 2: Extended variations on top 2 angles
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- Wave 3: Wild card angles (contrarian, emotional, specific)
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### 3. Quality filter
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- Remove anything over character limit
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- Remove duplicates or near-duplicates
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- Flag anything that might violate platform policies
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- Ensure headline/description combinations make sense together
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---
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## Common Mistakes
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- **Writing headlines that only work together** — RSA headlines get combined randomly
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- **Ignoring character limits** — Platforms truncate without warning
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- **All variations sound the same** — Vary angles, not just word choice
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- **No CTA headlines** — Always include action-oriented headlines
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- **Generic descriptions** — "Learn more about our solution" wastes the slot
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- **Iterating without data** — Gut feelings are less reliable than metrics
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- **Testing too many things at once** — Change one variable per test cycle
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- **Retiring creative too early** — Allow 1,000+ impressions before judging
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---
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## Tool Integrations
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For pulling performance data and managing campaigns, see the [tools registry](../../tools/REGISTRY.md).
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| Platform | Pull Performance Data | Manage Campaigns | Guide |
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|----------|:---------------------:|:----------------:|-------|
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| **Google Ads** | `google-ads campaigns list`, `google-ads reports get` | `google-ads campaigns create` | [google-ads.md](../../tools/integrations/google-ads.md) |
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| **Meta Ads** | `meta-ads insights get` | `meta-ads campaigns list` | [meta-ads.md](../../tools/integrations/meta-ads.md) |
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| **LinkedIn Ads** | `linkedin-ads analytics get` | `linkedin-ads campaigns list` | [linkedin-ads.md](../../tools/integrations/linkedin-ads.md) |
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| **TikTok Ads** | `tiktok-ads reports get` | `tiktok-ads campaigns list` | [tiktok-ads.md](../../tools/integrations/tiktok-ads.md) |
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### Workflow: Pull Data, Analyze, Generate
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```bash
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# 1. Pull recent ad performance
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node tools/clis/google-ads.js reports get --type ad_performance --date-range last_30_days
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# 2. Analyze output (identify top/bottom performers)
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# 3. Feed winning patterns into this skill
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# 4. Generate new variations
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# 5. Upload to platform
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```
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---
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## Related Skills
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- **paid-ads**: For campaign strategy, targeting, budgets, and optimization
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- **copywriting**: For landing page copy (where ad traffic lands)
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- **ab-test-setup**: For structuring creative tests with statistical rigor
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- **marketing-psychology**: For psychological principles behind high-performing creative
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- **copy-editing**: For polishing ad copy before launch
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637
skills/ad-creative/references/generative-tools.md
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637
skills/ad-creative/references/generative-tools.md
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# Generative AI Tools for Ad Creative
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Reference for using AI image generators, video generators, and code-based video tools to produce ad visuals at scale.
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---
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## When to Use Generative Tools
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| Need | Tool Category | Best Fit |
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|------|---------------|----------|
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| Static ad images (banners, social) | Image generation | Nano Banana Pro, Flux, Ideogram |
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| Ad images with text overlays | Image generation (text-capable) | Ideogram, Nano Banana Pro |
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| Short video ads (6-30 sec) | Video generation | Veo, Kling, Runway, Sora, Seedance |
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| Video ads with voiceover | Video gen + voice | Veo/Sora (native), or Runway + ElevenLabs |
|
||||
| Voiceover tracks for ads | Voice generation | ElevenLabs, OpenAI TTS, Cartesia |
|
||||
| Multi-language ad versions | Voice generation | ElevenLabs, PlayHT |
|
||||
| Brand voice cloning | Voice generation | ElevenLabs, Resemble AI |
|
||||
| Product mockups and variations | Image generation + references | Flux (multi-image reference) |
|
||||
| Templated video ads at scale | Code-based video | Remotion |
|
||||
| Personalized video (name, data) | Code-based video | Remotion |
|
||||
| Brand-consistent variations | Image gen + style refs | Flux, Ideogram, Nano Banana Pro |
|
||||
|
||||
---
|
||||
|
||||
## Image Generation
|
||||
|
||||
### Nano Banana Pro (Gemini)
|
||||
|
||||
Google DeepMind's image generation model, available through the Gemini API.
|
||||
|
||||
**Best for:** High-quality ad images, product visuals, text rendering
|
||||
**API:** Gemini API (Google AI Studio, Vertex AI)
|
||||
**Pricing:** ~$0.04/image (Gemini 2.5 Flash Image), ~$0.24/4K image (Nano Banana Pro)
|
||||
|
||||
**Strengths:**
|
||||
- Strong text rendering in images (logos, headlines)
|
||||
- Native image editing (modify existing images with prompts)
|
||||
- Available through the same Gemini API used for text generation
|
||||
- Supports both generation and editing in one model
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Generate social media ad images from text descriptions
|
||||
- Create product mockup variations
|
||||
- Edit existing ad images (swap backgrounds, change colors)
|
||||
- Generate images with headline text baked in
|
||||
|
||||
**API example:**
|
||||
```bash
|
||||
# Using the Gemini API for image generation
|
||||
curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "x-goog-api-key: $GEMINI_API_KEY" \
|
||||
-d '{
|
||||
"contents": [{"parts": [{"text": "Create a clean, modern social media ad image for a project management tool. Show a laptop with a kanban board interface. Bright, professional, 16:9 ratio."}]}],
|
||||
"generationConfig": {"responseModalities": ["TEXT", "IMAGE"]}
|
||||
}'
|
||||
```
|
||||
|
||||
**Docs:** [Gemini Image Generation](https://ai.google.dev/gemini-api/docs/image-generation)
|
||||
|
||||
---
|
||||
|
||||
### Flux (Black Forest Labs)
|
||||
|
||||
Open-weight image generation models with API access through Replicate and BFL's native API.
|
||||
|
||||
**Best for:** Photorealistic images, brand-consistent variations, multi-reference generation
|
||||
**API:** Replicate, BFL API, fal.ai
|
||||
**Pricing:** ~$0.01-0.06/image depending on model and resolution
|
||||
|
||||
**Model variants:**
|
||||
| Model | Speed | Quality | Cost | Best For |
|
||||
|-------|-------|---------|------|----------|
|
||||
| Flux 2 Pro | ~6 sec | Highest | $0.015/MP | Final production assets |
|
||||
| Flux 2 Flex | ~22 sec | High + editing | $0.06/MP | Iterative editing |
|
||||
| Flux 2 Dev | ~2.5 sec | Good | $0.012/MP | Rapid prototyping |
|
||||
| Flux 2 Klein | Fastest | Good | Lowest | High-volume batch generation |
|
||||
|
||||
**Strengths:**
|
||||
- Multi-image reference (up to 8 images) for consistent identity across ads
|
||||
- Product consistency — same product in different contexts
|
||||
- Style transfer from reference images
|
||||
- Open-weight Dev model for self-hosting
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Generate 50+ ad variations with consistent product/person identity
|
||||
- Create product-in-context images (your SaaS on different devices)
|
||||
- Style-match to existing brand assets using reference images
|
||||
- Rapid A/B test image variations
|
||||
|
||||
**Docs:** [Replicate Flux](https://replicate.com/black-forest-labs/flux-2-pro), [BFL API](https://docs.bfl.ml/)
|
||||
|
||||
---
|
||||
|
||||
### Ideogram
|
||||
|
||||
Specialized in typography and text rendering within images.
|
||||
|
||||
**Best for:** Ad banners with text, branded graphics, social ad images with headlines
|
||||
**API:** Ideogram API, Runware
|
||||
**Pricing:** ~$0.06/image (API), ~$0.009/image (subscription)
|
||||
|
||||
**Strengths:**
|
||||
- Best-in-class text rendering (~90% accuracy vs ~30% for most tools)
|
||||
- Style reference system (upload up to 3 reference images)
|
||||
- 4.3 billion style presets for consistent brand aesthetics
|
||||
- Strong at logos and branded typography
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Generate ad banners with headline text directly in the image
|
||||
- Create social media graphics with branded text overlays
|
||||
- Produce multiple design variations with consistent typography
|
||||
- Generate promotional materials without needing a designer for each iteration
|
||||
|
||||
**Docs:** [Ideogram API](https://developer.ideogram.ai/), [Ideogram](https://ideogram.ai/)
|
||||
|
||||
---
|
||||
|
||||
### Other Image Tools
|
||||
|
||||
| Tool | Best For | API Status | Notes |
|
||||
|------|----------|------------|-------|
|
||||
| **DALL-E 3** (OpenAI) | General image generation | Official API | Integrated with ChatGPT, good text rendering |
|
||||
| **Midjourney** | Artistic, high-aesthetic images | No official public API | Discord-based; unofficial APIs exist but risk bans |
|
||||
| **Stable Diffusion** | Self-hosted, customizable | Open source | Best for teams with GPU infrastructure |
|
||||
|
||||
---
|
||||
|
||||
## Video Generation
|
||||
|
||||
### Google Veo
|
||||
|
||||
Google DeepMind's video generation model, available through the Gemini API and Vertex AI.
|
||||
|
||||
**Best for:** High-quality video ads with native audio, vertical video for social
|
||||
**API:** Gemini API, Vertex AI
|
||||
**Pricing:** ~$0.15/sec (Veo 3.1 Fast), ~$0.40/sec (Veo 3.1 Standard)
|
||||
|
||||
**Capabilities:**
|
||||
- Up to 60 seconds at 1080p
|
||||
- Native audio generation (dialogue, sound effects, ambient)
|
||||
- Vertical 9:16 output for Stories/Reels/Shorts
|
||||
- Upscale to 4K
|
||||
- Text-to-video and image-to-video
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Generate short video ads (15-30 sec) from text descriptions
|
||||
- Create vertical video ads for TikTok, Reels, Shorts
|
||||
- Produce product demos with voiceover
|
||||
- Generate multiple video variations from the same prompt with different styles
|
||||
|
||||
**Docs:** [Veo on Vertex AI](https://cloud.google.com/vertex-ai/generative-ai/docs/video/overview)
|
||||
|
||||
---
|
||||
|
||||
### Kling (Kuaishou)
|
||||
|
||||
Video generation with simultaneous audio-visual generation and camera controls.
|
||||
|
||||
**Best for:** Cinematic video ads, longer-form content, audio-synced video
|
||||
**API:** Kling API, PiAPI, fal.ai
|
||||
**Pricing:** ~$0.09/sec (via fal.ai third-party)
|
||||
|
||||
**Capabilities:**
|
||||
- Up to 3 minutes at 1080p/30-48fps
|
||||
- Simultaneous audio-visual generation (Kling 2.6)
|
||||
- Text-to-video and image-to-video
|
||||
- Motion and camera controls
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Longer product explainer videos
|
||||
- Cinematic brand videos with synchronized audio
|
||||
- Animate product images into video ads
|
||||
|
||||
**Docs:** [Kling AI Developer](https://klingai.com/global/dev/model/video)
|
||||
|
||||
---
|
||||
|
||||
### Runway
|
||||
|
||||
Video generation and editing platform with strong controllability.
|
||||
|
||||
**Best for:** Controlled video generation, style-consistent content, editing existing footage
|
||||
**API:** Runway Developer Portal
|
||||
|
||||
**Capabilities:**
|
||||
- Gen-4: Character/scene consistency across shots
|
||||
- Motion brush and camera controls
|
||||
- Image-to-video with reference images
|
||||
- Video-to-video style transfer
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Generate video ads with consistent characters/products across scenes
|
||||
- Style-transfer existing footage to match brand aesthetics
|
||||
- Extend or remix existing video content
|
||||
|
||||
**Docs:** [Runway API](https://docs.dev.runwayml.com/)
|
||||
|
||||
---
|
||||
|
||||
### Sora 2 (OpenAI)
|
||||
|
||||
OpenAI's video generation model with synchronized audio.
|
||||
|
||||
**Best for:** High-fidelity video with dialogue and sound
|
||||
**API:** OpenAI API
|
||||
**Pricing:** Free tier available; Pro from $0.10-0.50/sec depending on resolution
|
||||
|
||||
**Capabilities:**
|
||||
- Up to 60 seconds with synchronized audio
|
||||
- Dialogue, sound effects, and ambient audio
|
||||
- sora-2 (fast) and sora-2-pro (quality) variants
|
||||
- Text-to-video and image-to-video
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Video testimonials and talking-head style ads
|
||||
- Product demo videos with narration
|
||||
- Narrative brand videos
|
||||
|
||||
**Docs:** [OpenAI Video Generation](https://platform.openai.com/docs/guides/video-generation)
|
||||
|
||||
---
|
||||
|
||||
### Seedance 2.0 (ByteDance)
|
||||
|
||||
ByteDance's video generation model with simultaneous audio-visual generation and multimodal inputs.
|
||||
|
||||
**Best for:** Fast, affordable video ads with native audio, multimodal reference inputs
|
||||
**API:** BytePlus (official), Replicate, WaveSpeedAI, fal.ai (third-party); OpenAI-compatible API format
|
||||
**Pricing:** ~$0.10-0.80/min depending on resolution (estimated 10-100x cheaper than Sora 2 per clip)
|
||||
|
||||
**Capabilities:**
|
||||
- Up to 20 seconds at up to 2K resolution
|
||||
- Simultaneous audio-visual generation (Dual-Branch Diffusion Transformer)
|
||||
- Text-to-video and image-to-video
|
||||
- Up to 12 reference files for multimodal input
|
||||
- OpenAI-compatible API structure
|
||||
|
||||
**Ad creative use cases:**
|
||||
- High-volume short video ad production at low cost
|
||||
- Video ads with synchronized voiceover and sound effects in one pass
|
||||
- Multi-reference generation (feed product images, brand assets, style references)
|
||||
- Rapid iteration on video ad concepts
|
||||
|
||||
**Docs:** [Seedance](https://seed.bytedance.com/en/seedance2_0)
|
||||
|
||||
---
|
||||
|
||||
### Higgsfield
|
||||
|
||||
Full-stack video creation platform with cinematic camera controls.
|
||||
|
||||
**Best for:** Social video ads, cinematic style, mobile-first content
|
||||
**Platform:** [higgsfield.ai](https://higgsfield.ai/)
|
||||
|
||||
**Capabilities:**
|
||||
- 50+ professional camera movements (zooms, pans, FPV drone shots)
|
||||
- Image-to-video animation
|
||||
- Built-in editing, transitions, and keyframing
|
||||
- All-in-one workflow: image gen, animation, editing
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Social media video ads with cinematic feel
|
||||
- Animate product images into dynamic video
|
||||
- Create multiple video variations with different camera styles
|
||||
- Quick-turn video content for social campaigns
|
||||
|
||||
---
|
||||
|
||||
### Video Tool Comparison
|
||||
|
||||
| Tool | Max Length | Audio | Resolution | API | Best For |
|
||||
|------|-----------|-------|------------|-----|----------|
|
||||
| **Veo 3.1** | 60 sec | Native | 1080p/4K | Gemini | Vertical social video |
|
||||
| **Kling 2.6** | 3 min | Native | 1080p | Third-party | Longer cinematic |
|
||||
| **Runway Gen-4** | 10 sec | No | 1080p | Official | Controlled, consistent |
|
||||
| **Sora 2** | 60 sec | Native | 1080p | Official | Dialogue-heavy |
|
||||
| **Seedance 2.0** | 20 sec | Native | 2K | Official + third-party | Affordable high-volume |
|
||||
| **Higgsfield** | Varies | Yes | 1080p | Web-based | Social, mobile-first |
|
||||
|
||||
---
|
||||
|
||||
## Voice & Audio Generation
|
||||
|
||||
For layering realistic voiceovers onto video ads, adding narration to product demos, or generating audio for Remotion-rendered videos. These tools turn ad scripts into natural-sounding voice tracks.
|
||||
|
||||
### When to Use Voice Tools
|
||||
|
||||
Many video generators (Veo, Kling, Sora, Seedance) now include native audio. Use standalone voice tools when you need:
|
||||
|
||||
- **Voiceover on silent video** — Runway Gen-4 and Remotion produce silent output
|
||||
- **Brand voice consistency** — Clone a specific voice for all ads
|
||||
- **Multi-language versions** — Same ad script in 20+ languages
|
||||
- **Script iteration** — Re-record voiceover without reshooting video
|
||||
- **Precise control** — Exact timing, emotion, and pacing
|
||||
|
||||
---
|
||||
|
||||
### ElevenLabs
|
||||
|
||||
The market leader in realistic voice generation and voice cloning.
|
||||
|
||||
**Best for:** Most natural-sounding voiceovers, brand voice cloning, multilingual
|
||||
**API:** REST API with streaming support
|
||||
**Pricing:** ~$0.12-0.30 per 1,000 characters depending on plan; starts at $5/month
|
||||
|
||||
**Capabilities:**
|
||||
- 29+ languages with natural accent and intonation
|
||||
- Voice cloning from short audio clips (instant) or longer recordings (professional)
|
||||
- Emotion and style control
|
||||
- Streaming for real-time generation
|
||||
- Voice library with hundreds of pre-built voices
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Generate voiceover tracks for video ads
|
||||
- Clone your brand spokesperson's voice for all ad variations
|
||||
- Produce the same ad in 10+ languages from one script
|
||||
- A/B test different voice styles (authoritative vs. friendly vs. urgent)
|
||||
|
||||
**API example:**
|
||||
```bash
|
||||
curl -X POST "https://api.elevenlabs.io/v1/text-to-speech/{voice_id}" \
|
||||
-H "xi-api-key: $ELEVENLABS_API_KEY" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"text": "Stop wasting hours on manual reporting. Try DataFlow free for 14 days.",
|
||||
"model_id": "eleven_multilingual_v2",
|
||||
"voice_settings": {"stability": 0.5, "similarity_boost": 0.75}
|
||||
}' --output voiceover.mp3
|
||||
```
|
||||
|
||||
**Docs:** [ElevenLabs API](https://elevenlabs.io/docs/api-reference/text-to-speech)
|
||||
|
||||
---
|
||||
|
||||
### OpenAI TTS
|
||||
|
||||
Simple, affordable text-to-speech built into the OpenAI API.
|
||||
|
||||
**Best for:** Quick voiceovers, cost-effective at scale, simple integration
|
||||
**API:** OpenAI API (same SDK as GPT/DALL-E)
|
||||
**Pricing:** $15/million chars (standard), $30/million chars (HD); ~$0.015/min with gpt-4o-mini-tts
|
||||
|
||||
**Capabilities:**
|
||||
- 13 built-in voices (no custom cloning)
|
||||
- Multiple languages
|
||||
- Real-time streaming
|
||||
- HD quality option
|
||||
- Simple API — same SDK you already use for GPT
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Fast, cheap voiceover for draft/test ad versions
|
||||
- High-volume narration at low cost
|
||||
- Prototype ad audio before investing in premium voice
|
||||
|
||||
**Docs:** [OpenAI TTS](https://platform.openai.com/docs/guides/text-to-speech)
|
||||
|
||||
---
|
||||
|
||||
### Cartesia Sonic
|
||||
|
||||
Ultra-low latency voice generation built for real-time applications.
|
||||
|
||||
**Best for:** Real-time voice, lowest latency, emotional expressiveness
|
||||
**API:** REST + WebSocket streaming
|
||||
**Pricing:** Starts at $5/month; pay-as-you-go from $0.03/min
|
||||
|
||||
**Capabilities:**
|
||||
- 40ms time-to-first-audio (fastest in class)
|
||||
- 15+ languages
|
||||
- Nonverbal expressiveness: laughter, breathing, emotional inflections
|
||||
- Sonic Turbo for even lower latency
|
||||
- Streaming API for real-time generation
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Real-time ad preview during creative iteration
|
||||
- Interactive demo videos with dynamic narration
|
||||
- Ads requiring natural laughter, sighs, or emotional reactions
|
||||
|
||||
**Docs:** [Cartesia Sonic](https://docs.cartesia.ai/build-with-cartesia/tts-models/latest)
|
||||
|
||||
---
|
||||
|
||||
### Voicebox (Open Source)
|
||||
|
||||
Free, local-first voice synthesis studio powered by Qwen3-TTS. The open-source alternative to ElevenLabs.
|
||||
|
||||
**Best for:** Free voice cloning, local/private generation, zero-cost batch production
|
||||
**API:** Local REST API at `http://localhost:8000`
|
||||
**Pricing:** Free (MIT license). Runs entirely on your machine.
|
||||
**Stack:** Tauri (Rust) + React + FastAPI (Python)
|
||||
|
||||
**Capabilities:**
|
||||
- Voice cloning from short audio samples via Qwen3-TTS
|
||||
- Multi-language support (English, Chinese, more planned)
|
||||
- Multi-track timeline editor for composing conversations
|
||||
- 4-5x faster inference on Apple Silicon via MLX Metal acceleration
|
||||
- Local REST API for programmatic generation
|
||||
- No cloud dependency — all processing on-device
|
||||
|
||||
**Ad creative use cases:**
|
||||
- Free voice cloning for brand spokesperson across all ad variations
|
||||
- Batch generate voiceovers without per-character costs
|
||||
- Private/local generation when ad content is sensitive or pre-launch
|
||||
- Prototype voice variations before committing to a paid service
|
||||
|
||||
**API example:**
|
||||
```bash
|
||||
curl -X POST http://localhost:8000/generate \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"text": "Stop wasting hours on manual reporting.", "profile_id": "abc123", "language": "en"}'
|
||||
```
|
||||
|
||||
**Install:** Desktop apps for macOS and Windows at [voicebox.sh](https://voicebox.sh), or build from source:
|
||||
```bash
|
||||
git clone https://github.com/jamiepine/voicebox.git
|
||||
cd voicebox && make setup && make dev
|
||||
```
|
||||
|
||||
**Docs:** [GitHub](https://github.com/jamiepine/voicebox)
|
||||
|
||||
---
|
||||
|
||||
### Other Voice Tools
|
||||
|
||||
| Tool | Best For | Differentiator | API |
|
||||
|------|----------|---------------|-----|
|
||||
| **PlayHT** | Large voice library, low latency | 900+ voices, <300ms latency, ultra-realistic | [play.ht](https://play.ht/) |
|
||||
| **Resemble AI** | Enterprise voice cloning | On-premise deployment, real-time speech-to-speech | [resemble.ai](https://www.resemble.ai/) |
|
||||
| **WellSaid Labs** | Ethical, commercial-safe voices | Voices from compensated actors, safe for commercial use | [wellsaid.io](https://www.wellsaid.io/) |
|
||||
| **Fish Audio** | Budget-friendly, emotion control | ~50-70% cheaper than ElevenLabs, emotion tags | [fish.audio](https://fish.audio/) |
|
||||
| **Murf AI** | Non-technical teams | Browser-based studio, 200+ voices | [murf.ai](https://murf.ai/) |
|
||||
| **Google Cloud TTS** | Google ecosystem, scale | 220+ voices, 40+ languages, enterprise SLAs | [Google TTS](https://cloud.google.com/text-to-speech) |
|
||||
| **Amazon Polly** | AWS ecosystem, cost | Neural voices, SSML control, cheap at volume | [Amazon Polly](https://aws.amazon.com/polly/) |
|
||||
|
||||
---
|
||||
|
||||
### Voice Tool Comparison
|
||||
|
||||
| Tool | Quality | Cloning | Languages | Latency | Price/1K chars |
|
||||
|------|---------|---------|-----------|---------|----------------|
|
||||
| **ElevenLabs** | Best | Yes (instant + pro) | 29+ | ~200ms | $0.12-0.30 |
|
||||
| **OpenAI TTS** | Good | No | 13+ | ~300ms | $0.015-0.030 |
|
||||
| **Cartesia Sonic** | Very good | No | 15+ | ~40ms | ~$0.03/min |
|
||||
| **PlayHT** | Very good | Yes | 140+ | <300ms | ~$0.10-0.20 |
|
||||
| **Fish Audio** | Good | Yes | 13+ | ~200ms | ~$0.05-0.10 |
|
||||
| **WellSaid** | Very good | No (actor voices) | English | ~300ms | Custom pricing |
|
||||
| **Voicebox** | Good | Yes (local) | 2+ | Local | Free (open source) |
|
||||
|
||||
### Choosing a Voice Tool
|
||||
|
||||
```
|
||||
Need voiceover for ads?
|
||||
├── Need to clone a specific brand voice?
|
||||
│ ├── Best quality → ElevenLabs
|
||||
│ ├── Enterprise/on-premise → Resemble AI
|
||||
│ └── Budget-friendly → Fish Audio, PlayHT
|
||||
├── Need multilingual (same ad, many languages)?
|
||||
│ ├── Most languages → PlayHT (140+)
|
||||
│ └── Best quality → ElevenLabs (29+)
|
||||
├── Need free / open source / local?
|
||||
│ └── Voicebox (MIT, runs on your machine)
|
||||
├── Need cheap, fast, good-enough?
|
||||
│ └── OpenAI TTS ($0.015/min)
|
||||
├── Need commercially-safe licensing?
|
||||
│ └── WellSaid Labs (actor-compensated voices)
|
||||
└── Need real-time/interactive?
|
||||
└── Cartesia Sonic (40ms TTFA)
|
||||
```
|
||||
|
||||
### Workflow: Voice + Video
|
||||
|
||||
```
|
||||
1. Write ad script (use ad-creative skill for copy)
|
||||
2. Generate voiceover with ElevenLabs/OpenAI TTS
|
||||
3. Generate or render video:
|
||||
a. Silent video from Runway/Remotion → layer voice track
|
||||
b. Or use Veo/Sora/Seedance with native audio (skip separate VO)
|
||||
4. Combine with ffmpeg if layering separately:
|
||||
ffmpeg -i video.mp4 -i voiceover.mp3 -c:v copy -c:a aac output.mp4
|
||||
5. Generate variations (different scripts, voices, or languages)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Code-Based Video: Remotion
|
||||
|
||||
For templated, data-driven video ads at scale, Remotion is the best option. Unlike AI video generators that produce unique video from prompts, Remotion uses React code to render deterministic, brand-perfect video from templates and data.
|
||||
|
||||
**Best for:** Templated ad variations, personalized video, brand-consistent production
|
||||
**Stack:** React + TypeScript
|
||||
**Pricing:** Free for individuals/small teams; commercial license required for 4+ employees
|
||||
**Docs:** [remotion.dev](https://www.remotion.dev/)
|
||||
|
||||
### Why Remotion for Ads
|
||||
|
||||
| AI Video Generators | Remotion |
|
||||
|---------------------|----------|
|
||||
| Unique output each time | Deterministic, pixel-perfect |
|
||||
| Prompt-based, less control | Full code control over every frame |
|
||||
| Hard to match brand exactly | Exact brand colors, fonts, spacing |
|
||||
| One-at-a-time generation | Batch render hundreds from data |
|
||||
| No dynamic data insertion | Personalize with names, prices, stats |
|
||||
|
||||
### Ad Creative Use Cases
|
||||
|
||||
**1. Dynamic product ads**
|
||||
Feed a JSON array of products and render a unique video ad for each:
|
||||
```tsx
|
||||
// Simplified Remotion component for product ads
|
||||
export const ProductAd: React.FC<{
|
||||
productName: string;
|
||||
price: string;
|
||||
imageUrl: string;
|
||||
tagline: string;
|
||||
}> = ({productName, price, imageUrl, tagline}) => {
|
||||
return (
|
||||
<AbsoluteFill style={{backgroundColor: '#fff'}}>
|
||||
<Img src={imageUrl} style={{width: 400, height: 400}} />
|
||||
<h1>{productName}</h1>
|
||||
<p>{tagline}</p>
|
||||
<div className="price">{price}</div>
|
||||
<div className="cta">Shop Now</div>
|
||||
</AbsoluteFill>
|
||||
);
|
||||
};
|
||||
```
|
||||
|
||||
**2. A/B test video variations**
|
||||
Render the same template with different headlines, CTAs, or color schemes:
|
||||
```tsx
|
||||
const variations = [
|
||||
{headline: "Save 50% Today", cta: "Get the Deal", theme: "urgent"},
|
||||
{headline: "Join 10K+ Teams", cta: "Start Free", theme: "social-proof"},
|
||||
{headline: "Built for Speed", cta: "Try It Now", theme: "benefit"},
|
||||
];
|
||||
// Render all variations programmatically
|
||||
```
|
||||
|
||||
**3. Personalized outreach videos**
|
||||
Generate videos addressing prospects by name for cold outreach or sales.
|
||||
|
||||
**4. Social ad batch production**
|
||||
Render the same content across different aspect ratios:
|
||||
- 1:1 for feed
|
||||
- 9:16 for Stories/Reels
|
||||
- 16:9 for YouTube
|
||||
|
||||
### Remotion Workflow for Ad Creative
|
||||
|
||||
```
|
||||
1. Design template in React (or use AI to generate the component)
|
||||
2. Define data schema (products, headlines, CTAs, images)
|
||||
3. Feed data array into template
|
||||
4. Batch render all variations
|
||||
5. Upload to ad platform
|
||||
```
|
||||
|
||||
### Getting Started
|
||||
|
||||
```bash
|
||||
# Create a new Remotion project
|
||||
npx create-video@latest
|
||||
|
||||
# Render a single video
|
||||
npx remotion render src/index.ts MyComposition out/video.mp4
|
||||
|
||||
# Batch render from data
|
||||
npx remotion render src/index.ts MyComposition --props='{"data": [...]}'
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Choosing the Right Tool
|
||||
|
||||
### Decision Tree
|
||||
|
||||
```
|
||||
Need video ads?
|
||||
├── Templated, data-driven (same structure, different data)
|
||||
│ └── Use Remotion
|
||||
├── Unique creative from prompts (exploratory)
|
||||
│ ├── Need dialogue/voiceover? → Sora 2, Veo 3.1, Kling 2.6, Seedance 2.0
|
||||
│ ├── Need consistency across scenes? → Runway Gen-4
|
||||
│ ├── Need vertical social video? → Veo 3.1 (native 9:16)
|
||||
│ ├── Need high volume at low cost? → Seedance 2.0
|
||||
│ └── Need cinematic camera work? → Higgsfield, Kling
|
||||
└── Both → Use AI gen for hero creative, Remotion for variations
|
||||
|
||||
Need image ads?
|
||||
├── Need text/headlines in image? → Ideogram
|
||||
├── Need product consistency across variations? → Flux (multi-ref)
|
||||
├── Need quick iterations on existing images? → Nano Banana Pro
|
||||
├── Need highest visual quality? → Flux Pro, Midjourney
|
||||
└── Need high volume at low cost? → Flux Klein, Nano Banana
|
||||
```
|
||||
|
||||
### Cost Comparison for 100 Ad Variations
|
||||
|
||||
| Approach | Tool | Approximate Cost |
|
||||
|----------|------|-----------------|
|
||||
| 100 static images | Nano Banana Pro | ~$4-24 |
|
||||
| 100 static images | Flux Dev | ~$1-2 |
|
||||
| 100 static images | Ideogram API | ~$6 |
|
||||
| 100 × 15-sec videos | Veo 3.1 Fast | ~$225 |
|
||||
| 100 × 15-sec videos | Remotion (templated) | ~$0 (self-hosted render) |
|
||||
| 10 hero videos + 90 templated | Veo + Remotion | ~$22 + render time |
|
||||
|
||||
### Recommended Workflow for Scaled Ad Production
|
||||
|
||||
1. **Generate hero creative** with AI (Nano Banana, Flux, Veo) — high-quality, exploratory
|
||||
2. **Build templates** in Remotion based on winning creative patterns
|
||||
3. **Batch produce variations** with Remotion using data (products, headlines, CTAs)
|
||||
4. **Iterate** — use AI tools for new angles, Remotion for scale
|
||||
|
||||
This hybrid approach gives you the creative exploration of AI generators and the consistency and scale of code-based rendering.
|
||||
|
||||
---
|
||||
|
||||
## Platform-Specific Image Specs
|
||||
|
||||
When generating images for ads, request the correct dimensions:
|
||||
|
||||
| Platform | Placement | Aspect Ratio | Recommended Size |
|
||||
|----------|-----------|-------------|-----------------|
|
||||
| Meta Feed | Single image | 1:1 | 1080x1080 |
|
||||
| Meta Stories/Reels | Vertical | 9:16 | 1080x1920 |
|
||||
| Meta Carousel | Square | 1:1 | 1080x1080 |
|
||||
| Google Display | Landscape | 1.91:1 | 1200x628 |
|
||||
| Google Display | Square | 1:1 | 1200x1200 |
|
||||
| LinkedIn Feed | Landscape | 1.91:1 | 1200x627 |
|
||||
| LinkedIn Feed | Square | 1:1 | 1200x1200 |
|
||||
| TikTok Feed | Vertical | 9:16 | 1080x1920 |
|
||||
| Twitter/X Feed | Landscape | 16:9 | 1200x675 |
|
||||
| Twitter/X Card | Landscape | 1.91:1 | 800x418 |
|
||||
|
||||
Include these dimensions in your generation prompts to avoid needing to crop or resize.
|
||||
213
skills/ad-creative/references/platform-specs.md
Normal file
213
skills/ad-creative/references/platform-specs.md
Normal file
|
|
@ -0,0 +1,213 @@
|
|||
# Platform Specs Reference
|
||||
|
||||
Complete character limits, format requirements, and best practices for each ad platform.
|
||||
|
||||
---
|
||||
|
||||
## Google Ads
|
||||
|
||||
### Responsive Search Ads (RSAs)
|
||||
|
||||
| Element | Character Limit | Required | Notes |
|
||||
|---------|----------------|----------|-------|
|
||||
| Headline | 30 chars | 3 minimum, 15 max | Any 3 may be shown together |
|
||||
| Description | 90 chars | 2 minimum, 4 max | Any 2 may be shown together |
|
||||
| Display path 1 | 15 chars | Optional | Appears after domain in URL |
|
||||
| Display path 2 | 15 chars | Optional | Appears after path 1 |
|
||||
| Final URL | No limit | Required | Landing page URL |
|
||||
|
||||
**Combination rules:**
|
||||
- Google selects up to 3 headlines and 2 descriptions to show
|
||||
- Headlines appear separated by " | " or stacked
|
||||
- Any headline can appear in any position unless pinned
|
||||
- Pinning reduces Google's ability to optimize — use sparingly
|
||||
|
||||
**Pinning strategy:**
|
||||
- Pin your brand name to position 1 if brand guidelines require it
|
||||
- Pin your strongest CTA to position 2 or 3
|
||||
- Leave most headlines unpinned for machine learning
|
||||
|
||||
**Headline mix recommendation (15 headlines):**
|
||||
- 3-4 keyword-focused (match search intent)
|
||||
- 3-4 benefit-focused (what they get)
|
||||
- 2-3 social proof (numbers, awards, customers)
|
||||
- 2-3 CTA-focused (action to take)
|
||||
- 1-2 differentiators (why you over competitors)
|
||||
- 1 brand name headline
|
||||
|
||||
**Description mix recommendation (4 descriptions):**
|
||||
- 1 benefit + proof point
|
||||
- 1 feature + outcome
|
||||
- 1 social proof + CTA
|
||||
- 1 urgency/offer + CTA (if applicable)
|
||||
|
||||
### Performance Max
|
||||
|
||||
| Element | Character Limit | Notes |
|
||||
|---------|----------------|-------|
|
||||
| Headline | 30 chars (5 required) | Short headlines for various placements |
|
||||
| Long headline | 90 chars (5 required) | Used in display, video, discover |
|
||||
| Description | 90 chars (1 required, 5 max) | Accompany various ad formats |
|
||||
| Business name | 25 chars | Required |
|
||||
|
||||
### Display Ads
|
||||
|
||||
| Element | Character Limit |
|
||||
|---------|----------------|
|
||||
| Headline | 30 chars |
|
||||
| Long headline | 90 chars |
|
||||
| Description | 90 chars |
|
||||
| Business name | 25 chars |
|
||||
|
||||
---
|
||||
|
||||
## Meta Ads (Facebook & Instagram)
|
||||
|
||||
### Single Image / Video / Carousel
|
||||
|
||||
| Element | Recommended | Maximum | Notes |
|
||||
|---------|-------------|---------|-------|
|
||||
| Primary text | 125 chars | 2,200 chars | Text above image; truncated after ~125 |
|
||||
| Headline | 40 chars | 255 chars | Below image; truncated after ~40 |
|
||||
| Description | 30 chars | 255 chars | Below headline; may not show |
|
||||
| URL display link | 40 chars | N/A | Optional custom display URL |
|
||||
|
||||
**Placement-specific notes:**
|
||||
- **Feed**: All elements show; primary text most visible
|
||||
- **Stories/Reels**: Primary text overlaid; keep under 72 chars
|
||||
- **Right column**: Only headline visible; skip description
|
||||
- **Audience Network**: Varies by publisher
|
||||
|
||||
**Best practices:**
|
||||
- Front-load the hook in primary text (first 125 chars)
|
||||
- Use line breaks for readability in longer primary text
|
||||
- Emojis: test, but don't overuse — 1-2 per ad max
|
||||
- Questions in primary text increase engagement
|
||||
- Headline should be a clear CTA or value statement
|
||||
|
||||
### Lead Ads (Instant Form)
|
||||
|
||||
| Element | Limit |
|
||||
|---------|-------|
|
||||
| Greeting headline | 60 chars |
|
||||
| Greeting description | 360 chars |
|
||||
| Privacy policy text | 200 chars |
|
||||
|
||||
---
|
||||
|
||||
## LinkedIn Ads
|
||||
|
||||
### Single Image Ad
|
||||
|
||||
| Element | Recommended | Maximum | Notes |
|
||||
|---------|-------------|---------|-------|
|
||||
| Intro text | 150 chars | 600 chars | Above the image; truncated after ~150 |
|
||||
| Headline | 70 chars | 200 chars | Below the image |
|
||||
| Description | 100 chars | 300 chars | Only shows on Audience Network |
|
||||
|
||||
### Carousel Ad
|
||||
|
||||
| Element | Limit |
|
||||
|---------|-------|
|
||||
| Intro text | 255 chars |
|
||||
| Card headline | 45 chars |
|
||||
| Card count | 2-10 cards |
|
||||
|
||||
### Message Ad (InMail)
|
||||
|
||||
| Element | Limit |
|
||||
|---------|-------|
|
||||
| Subject line | 60 chars |
|
||||
| Message body | 1,500 chars |
|
||||
| CTA button | 20 chars |
|
||||
|
||||
### Text Ad
|
||||
|
||||
| Element | Limit |
|
||||
|---------|-------|
|
||||
| Headline | 25 chars |
|
||||
| Description | 75 chars |
|
||||
|
||||
**LinkedIn-specific guidelines:**
|
||||
- Professional tone, but not boring
|
||||
- Use job-specific language the audience recognizes
|
||||
- Statistics and data points perform well
|
||||
- Avoid consumer-style hype ("Amazing!" "Incredible!")
|
||||
- First-person testimonials from peers resonate
|
||||
|
||||
---
|
||||
|
||||
## TikTok Ads
|
||||
|
||||
### In-Feed Ads
|
||||
|
||||
| Element | Recommended | Maximum | Notes |
|
||||
|---------|-------------|---------|-------|
|
||||
| Ad text | 80 chars | 100 chars | Above the video |
|
||||
| Display name | N/A | 40 chars | Brand name |
|
||||
| CTA button | Platform options | Predefined | Select from TikTok's options |
|
||||
|
||||
### Spark Ads (Boosted Organic)
|
||||
|
||||
| Element | Notes |
|
||||
|---------|-------|
|
||||
| Caption | Uses original post caption |
|
||||
| CTA button | Added by advertiser |
|
||||
| Display name | Original creator's handle |
|
||||
|
||||
**TikTok-specific guidelines:**
|
||||
- Native content outperforms polished ads
|
||||
- First 2 seconds determine if they watch
|
||||
- Use trending sounds and formats
|
||||
- Text overlay is essential (most watch with sound off)
|
||||
- Vertical video only (9:16)
|
||||
|
||||
---
|
||||
|
||||
## Twitter/X Ads
|
||||
|
||||
### Promoted Tweets
|
||||
|
||||
| Element | Limit | Notes |
|
||||
|---------|-------|-------|
|
||||
| Tweet text | 280 chars | Full tweet with image/video |
|
||||
| Card headline | 70 chars | Website card |
|
||||
| Card description | 200 chars | Website card |
|
||||
|
||||
### Website Cards
|
||||
|
||||
| Element | Limit |
|
||||
|---------|-------|
|
||||
| Headline | 70 chars |
|
||||
| Description | 200 chars |
|
||||
|
||||
**Twitter/X-specific guidelines:**
|
||||
- Conversational, casual tone
|
||||
- Short sentences work best
|
||||
- One clear message per tweet
|
||||
- Hashtags: 1-2 max (0 is often better for ads)
|
||||
- Threads can work for consideration-stage content
|
||||
|
||||
---
|
||||
|
||||
## Character Counting Tips
|
||||
|
||||
- **Spaces count** as characters on all platforms
|
||||
- **Emojis** count as 1-2 characters depending on platform
|
||||
- **Special characters** (|, &, etc.) count as 1 character
|
||||
- **URLs** in body text count against limits
|
||||
- **Dynamic keyword insertion** (`{KeyWord:default}`) can exceed limits — set safe defaults
|
||||
- Always verify in the platform's ad preview before launching
|
||||
|
||||
---
|
||||
|
||||
## Multi-Platform Creative Adaptation
|
||||
|
||||
When creating for multiple platforms simultaneously, start with the most restrictive format:
|
||||
|
||||
1. **Google Search headlines** (30 chars) — forces the tightest messaging
|
||||
2. **Expand to Meta headlines** (40 chars) — add a word or two
|
||||
3. **Expand to LinkedIn intro text** (150 chars) — add context and proof
|
||||
4. **Expand to Meta primary text** (125+ chars) — full hook and value prop
|
||||
|
||||
This cascading approach ensures your core message works everywhere, then gets enriched for platforms that allow more space.
|
||||
398
skills/ai-seo/SKILL.md
Normal file
398
skills/ai-seo/SKILL.md
Normal file
|
|
@ -0,0 +1,398 @@
|
|||
---
|
||||
name: ai-seo
|
||||
description: "When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' or 'zero-click search.' This skill covers content optimization for AI answer engines, monitoring AI visibility, and getting cited as a source. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup."
|
||||
metadata:
|
||||
version: 1.0.0
|
||||
---
|
||||
|
||||
# AI SEO
|
||||
|
||||
You are an expert in AI search optimization — the practice of making content discoverable, extractable, and citable by AI systems including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Copilot. Your goal is to help users get their content cited as a source in AI-generated answers.
|
||||
|
||||
## Before Starting
|
||||
|
||||
**Check for product marketing context first:**
|
||||
If `.claude/product-marketing-context.md` exists, 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. Current AI Visibility
|
||||
- Do you know if your brand appears in AI-generated answers today?
|
||||
- Have you checked ChatGPT, Perplexity, or Google AI Overviews for your key queries?
|
||||
- What queries matter most to your business?
|
||||
|
||||
### 2. Content & Domain
|
||||
- What type of content do you produce? (Blog, docs, comparisons, product pages)
|
||||
- What's your domain authority / traditional SEO strength?
|
||||
- Do you have existing structured data (schema markup)?
|
||||
|
||||
### 3. Goals
|
||||
- Get cited as a source in AI answers?
|
||||
- Appear in Google AI Overviews for specific queries?
|
||||
- Compete with specific brands already getting cited?
|
||||
- Optimize existing content or create new AI-optimized content?
|
||||
|
||||
### 4. Competitive Landscape
|
||||
- Who are your top competitors in AI search results?
|
||||
- Are they being cited where you're not?
|
||||
|
||||
---
|
||||
|
||||
## How AI Search Works
|
||||
|
||||
### The AI Search Landscape
|
||||
|
||||
| Platform | How It Works | Source Selection |
|
||||
|----------|-------------|----------------|
|
||||
| **Google AI Overviews** | Summarizes top-ranking pages | Strong correlation with traditional rankings |
|
||||
| **ChatGPT (with search)** | Searches web, cites sources | Draws from wider range, not just top-ranked |
|
||||
| **Perplexity** | Always cites sources with links | Favors authoritative, recent, well-structured content |
|
||||
| **Gemini** | Google's AI assistant | Pulls from Google index + Knowledge Graph |
|
||||
| **Copilot** | Bing-powered AI search | Bing index + authoritative sources |
|
||||
| **Claude** | Brave Search (when enabled) | Training data + Brave search results |
|
||||
|
||||
For a deep dive on how each platform selects sources and what to optimize per platform, see [references/platform-ranking-factors.md](references/platform-ranking-factors.md).
|
||||
|
||||
### Key Difference from Traditional SEO
|
||||
|
||||
Traditional SEO gets you ranked. AI SEO gets you **cited**.
|
||||
|
||||
In traditional search, you need to rank on page 1. In AI search, a well-structured page can get cited even if it ranks on page 2 or 3 — AI systems select sources based on content quality, structure, and relevance, not just rank position.
|
||||
|
||||
**Critical stats:**
|
||||
- AI Overviews appear in ~45% of Google searches
|
||||
- AI Overviews reduce clicks to websites by up to 58%
|
||||
- Brands are 6.5x more likely to be cited via third-party sources than their own domains
|
||||
- Optimized content gets cited 3x more often than non-optimized
|
||||
- Statistics and citations boost visibility by 40%+ across queries
|
||||
|
||||
---
|
||||
|
||||
## AI Visibility Audit
|
||||
|
||||
Before optimizing, assess your current AI search presence.
|
||||
|
||||
### Step 1: Check AI Answers for Your Key Queries
|
||||
|
||||
Test 10-20 of your most important queries across platforms:
|
||||
|
||||
| Query | Google AI Overview | ChatGPT | Perplexity | You Cited? | Competitors Cited? |
|
||||
|-------|:-----------------:|:-------:|:----------:|:----------:|:-----------------:|
|
||||
| [query 1] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |
|
||||
| [query 2] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |
|
||||
|
||||
**Query types to test:**
|
||||
- "What is [your product category]?"
|
||||
- "Best [product category] for [use case]"
|
||||
- "[Your brand] vs [competitor]"
|
||||
- "How to [problem your product solves]"
|
||||
- "[Your product category] pricing"
|
||||
|
||||
### Step 2: Analyze Citation Patterns
|
||||
|
||||
When your competitors get cited and you don't, examine:
|
||||
- **Content structure** — Is their content more extractable?
|
||||
- **Authority signals** — Do they have more citations, stats, expert quotes?
|
||||
- **Freshness** — Is their content more recently updated?
|
||||
- **Schema markup** — Do they have structured data you're missing?
|
||||
- **Third-party presence** — Are they cited via Wikipedia, Reddit, review sites?
|
||||
|
||||
### Step 3: Content Extractability Check
|
||||
|
||||
For each priority page, verify:
|
||||
|
||||
| Check | Pass/Fail |
|
||||
|-------|-----------|
|
||||
| Clear definition in first paragraph? | |
|
||||
| Self-contained answer blocks (work without surrounding context)? | |
|
||||
| Statistics with sources cited? | |
|
||||
| Comparison tables for "[X] vs [Y]" queries? | |
|
||||
| FAQ section with natural-language questions? | |
|
||||
| Schema markup (FAQ, HowTo, Article, Product)? | |
|
||||
| Expert attribution (author name, credentials)? | |
|
||||
| Recently updated (within 6 months)? | |
|
||||
| Heading structure matches query patterns? | |
|
||||
| AI bots allowed in robots.txt? | |
|
||||
|
||||
### Step 4: AI Bot Access Check
|
||||
|
||||
Verify your robots.txt allows AI crawlers. Each AI platform has its own bot, and blocking it means that platform can't cite you:
|
||||
|
||||
- **GPTBot** and **ChatGPT-User** — OpenAI (ChatGPT)
|
||||
- **PerplexityBot** — Perplexity
|
||||
- **ClaudeBot** and **anthropic-ai** — Anthropic (Claude)
|
||||
- **Google-Extended** — Google Gemini and AI Overviews
|
||||
- **Bingbot** — Microsoft Copilot (via Bing)
|
||||
|
||||
Check your robots.txt for `Disallow` rules targeting any of these. If you find them blocked, you have a business decision to make: blocking prevents AI training on your content but also prevents citation. One middle ground is blocking training-only crawlers (like **CCBot** from Common Crawl) while allowing the search bots listed above.
|
||||
|
||||
See [references/platform-ranking-factors.md](references/platform-ranking-factors.md) for the full robots.txt configuration.
|
||||
|
||||
---
|
||||
|
||||
## Optimization Strategy
|
||||
|
||||
### The Three Pillars
|
||||
|
||||
```
|
||||
1. Structure (make it extractable)
|
||||
2. Authority (make it citable)
|
||||
3. Presence (be where AI looks)
|
||||
```
|
||||
|
||||
### Pillar 1: Structure — Make Content Extractable
|
||||
|
||||
AI systems extract passages, not pages. Every key claim should work as a standalone statement.
|
||||
|
||||
**Content block patterns:**
|
||||
- **Definition blocks** for "What is X?" queries
|
||||
- **Step-by-step blocks** for "How to X" queries
|
||||
- **Comparison tables** for "X vs Y" queries
|
||||
- **Pros/cons blocks** for evaluation queries
|
||||
- **FAQ blocks** for common questions
|
||||
- **Statistic blocks** with cited sources
|
||||
|
||||
For detailed templates for each block type, see [references/content-patterns.md](references/content-patterns.md).
|
||||
|
||||
**Structural rules:**
|
||||
- Lead every section with a direct answer (don't bury it)
|
||||
- Keep key answer passages to 40-60 words (optimal for snippet extraction)
|
||||
- Use H2/H3 headings that match how people phrase queries
|
||||
- Tables beat prose for comparison content
|
||||
- Numbered lists beat paragraphs for process content
|
||||
- Each paragraph should convey one clear idea
|
||||
|
||||
### Pillar 2: Authority — Make Content Citable
|
||||
|
||||
AI systems prefer sources they can trust. Build citation-worthiness.
|
||||
|
||||
**The Princeton GEO research** (KDD 2024, studied across Perplexity.ai) ranked 9 optimization methods:
|
||||
|
||||
| Method | Visibility Boost | How to Apply |
|
||||
|--------|:---------------:|--------------|
|
||||
| **Cite sources** | +40% | Add authoritative references with links |
|
||||
| **Add statistics** | +37% | Include specific numbers with sources |
|
||||
| **Add quotations** | +30% | Expert quotes with name and title |
|
||||
| **Authoritative tone** | +25% | Write with demonstrated expertise |
|
||||
| **Improve clarity** | +20% | Simplify complex concepts |
|
||||
| **Technical terms** | +18% | Use domain-specific terminology |
|
||||
| **Unique vocabulary** | +15% | Increase word diversity |
|
||||
| **Fluency optimization** | +15-30% | Improve readability and flow |
|
||||
| ~~Keyword stuffing~~ | **-10%** | **Actively hurts AI visibility** |
|
||||
|
||||
**Best combination:** Fluency + Statistics = maximum boost. Low-ranking sites benefit even more — up to 115% visibility increase with citations.
|
||||
|
||||
**Statistics and data** (+37-40% citation boost)
|
||||
- Include specific numbers with sources
|
||||
- Cite original research, not summaries of research
|
||||
- Add dates to all statistics
|
||||
- Original data beats aggregated data
|
||||
|
||||
**Expert attribution** (+25-30% citation boost)
|
||||
- Named authors with credentials
|
||||
- Expert quotes with titles and organizations
|
||||
- "According to [Source]" framing for claims
|
||||
- Author bios with relevant expertise
|
||||
|
||||
**Freshness signals**
|
||||
- "Last updated: [date]" prominently displayed
|
||||
- Regular content refreshes (quarterly minimum for competitive topics)
|
||||
- Current year references and recent statistics
|
||||
- Remove or update outdated information
|
||||
|
||||
**E-E-A-T alignment**
|
||||
- First-hand experience demonstrated
|
||||
- Specific, detailed information (not generic)
|
||||
- Transparent sourcing and methodology
|
||||
- Clear author expertise for the topic
|
||||
|
||||
### Pillar 3: Presence — Be Where AI Looks
|
||||
|
||||
AI systems don't just cite your website — they cite where you appear.
|
||||
|
||||
**Third-party sources matter more than your own site:**
|
||||
- Wikipedia mentions (7.8% of all ChatGPT citations)
|
||||
- Reddit discussions (1.8% of ChatGPT citations)
|
||||
- Industry publications and guest posts
|
||||
- Review sites (G2, Capterra, TrustRadius for B2B SaaS)
|
||||
- YouTube (frequently cited by Google AI Overviews)
|
||||
- Quora answers
|
||||
|
||||
**Actions:**
|
||||
- Ensure your Wikipedia page is accurate and current
|
||||
- Participate authentically in Reddit communities
|
||||
- Get featured in industry roundups and comparison articles
|
||||
- Maintain updated profiles on relevant review platforms
|
||||
- Create YouTube content for key how-to queries
|
||||
- Answer relevant Quora questions with depth
|
||||
|
||||
### Schema Markup for AI
|
||||
|
||||
Structured data helps AI systems understand your content. Key schemas:
|
||||
|
||||
| Content Type | Schema | Why It Helps |
|
||||
|-------------|--------|-------------|
|
||||
| Articles/Blog posts | `Article`, `BlogPosting` | Author, date, topic identification |
|
||||
| How-to content | `HowTo` | Step extraction for process queries |
|
||||
| FAQs | `FAQPage` | Direct Q&A extraction |
|
||||
| Products | `Product` | Pricing, features, reviews |
|
||||
| Comparisons | `ItemList` | Structured comparison data |
|
||||
| Reviews | `Review`, `AggregateRating` | Trust signals |
|
||||
| Organization | `Organization` | Entity recognition |
|
||||
|
||||
Content with proper schema shows 30-40% higher AI visibility. For implementation, use the **schema-markup** skill.
|
||||
|
||||
---
|
||||
|
||||
## Content Types That Get Cited Most
|
||||
|
||||
Not all content is equally citable. Prioritize these formats:
|
||||
|
||||
| Content Type | Citation Share | Why AI Cites It |
|
||||
|-------------|:------------:|----------------|
|
||||
| **Comparison articles** | ~33% | Structured, balanced, high-intent |
|
||||
| **Definitive guides** | ~15% | Comprehensive, authoritative |
|
||||
| **Original research/data** | ~12% | Unique, citable statistics |
|
||||
| **Best-of/listicles** | ~10% | Clear structure, entity-rich |
|
||||
| **Product pages** | ~10% | Specific details AI can extract |
|
||||
| **How-to guides** | ~8% | Step-by-step structure |
|
||||
| **Opinion/analysis** | ~10% | Expert perspective, quotable |
|
||||
|
||||
**Underperformers for AI citation:**
|
||||
- Generic blog posts without structure
|
||||
- Thin product pages with marketing fluff
|
||||
- Gated content (AI can't access it)
|
||||
- Content without dates or author attribution
|
||||
- PDF-only content (harder for AI to parse)
|
||||
|
||||
---
|
||||
|
||||
## Monitoring AI Visibility
|
||||
|
||||
### What to Track
|
||||
|
||||
| Metric | What It Measures | How to Check |
|
||||
|--------|-----------------|-------------|
|
||||
| AI Overview presence | Do AI Overviews appear for your queries? | Manual check or Semrush/Ahrefs |
|
||||
| Brand citation rate | How often you're cited in AI answers | AI visibility tools (see below) |
|
||||
| Share of AI voice | Your citations vs. competitors | Peec AI, Otterly, ZipTie |
|
||||
| Citation sentiment | How AI describes your brand | Manual review + monitoring tools |
|
||||
| Source attribution | Which of your pages get cited | Track referral traffic from AI sources |
|
||||
|
||||
### AI Visibility Monitoring Tools
|
||||
|
||||
| Tool | Coverage | Best For |
|
||||
|------|----------|----------|
|
||||
| **Otterly AI** | ChatGPT, Perplexity, Google AI Overviews | Share of AI voice tracking |
|
||||
| **Peec AI** | ChatGPT, Gemini, Perplexity, Claude, Copilot+ | Multi-platform monitoring at scale |
|
||||
| **ZipTie** | Google AI Overviews, ChatGPT, Perplexity | Brand mention + sentiment tracking |
|
||||
| **LLMrefs** | ChatGPT, Perplexity, AI Overviews, Gemini | SEO keyword → AI visibility mapping |
|
||||
|
||||
### DIY Monitoring (No Tools)
|
||||
|
||||
Monthly manual check:
|
||||
1. Pick your top 20 queries
|
||||
2. Run each through ChatGPT, Perplexity, and Google
|
||||
3. Record: Are you cited? Who is? What page?
|
||||
4. Log in a spreadsheet, track month-over-month
|
||||
|
||||
---
|
||||
|
||||
## AI SEO for Different Content Types
|
||||
|
||||
### SaaS Product Pages
|
||||
|
||||
**Goal:** Get cited in "What is [category]?" and "Best [category]" queries.
|
||||
|
||||
**Optimize:**
|
||||
- Clear product description in first paragraph (what it does, who it's for)
|
||||
- Feature comparison tables (you vs. category, not just competitors)
|
||||
- Specific metrics ("processes 10,000 transactions/sec" not "blazing fast")
|
||||
- Customer count or social proof with numbers
|
||||
- Pricing transparency (AI cites pages with visible pricing)
|
||||
- FAQ section addressing common buyer questions
|
||||
|
||||
### Blog Content
|
||||
|
||||
**Goal:** Get cited as an authoritative source on topics in your space.
|
||||
|
||||
**Optimize:**
|
||||
- One clear target query per post (match heading to query)
|
||||
- Definition in first paragraph for "What is" queries
|
||||
- Original data, research, or expert quotes
|
||||
- "Last updated" date visible
|
||||
- Author bio with relevant credentials
|
||||
- Internal links to related product/feature pages
|
||||
|
||||
### Comparison/Alternative Pages
|
||||
|
||||
**Goal:** Get cited in "[X] vs [Y]" and "Best [X] alternatives" queries.
|
||||
|
||||
**Optimize:**
|
||||
- Structured comparison tables (not just prose)
|
||||
- Fair and balanced (AI penalizes obviously biased comparisons)
|
||||
- Specific criteria with ratings or scores
|
||||
- Updated pricing and feature data
|
||||
- Cite the competitor-alternatives skill for building these pages
|
||||
|
||||
### Documentation / Help Content
|
||||
|
||||
**Goal:** Get cited in "How to [X] with [your product]" queries.
|
||||
|
||||
**Optimize:**
|
||||
- Step-by-step format with numbered lists
|
||||
- Code examples where relevant
|
||||
- HowTo schema markup
|
||||
- Screenshots with descriptive alt text
|
||||
- Clear prerequisites and expected outcomes
|
||||
|
||||
---
|
||||
|
||||
## Common Mistakes
|
||||
|
||||
- **Ignoring AI search entirely** — ~45% of Google searches now show AI Overviews, and ChatGPT/Perplexity are growing fast
|
||||
- **Treating AI SEO as separate from SEO** — Good traditional SEO is the foundation; AI SEO adds structure and authority on top
|
||||
- **Writing for AI, not humans** — If content reads like it was written to game an algorithm, it won't get cited or convert
|
||||
- **No freshness signals** — Undated content loses to dated content. Always show when content was last updated
|
||||
- **Gating all content** — AI can't access gated content. Keep your most authoritative content open
|
||||
- **Ignoring third-party presence** — You may get more AI citations from a Wikipedia mention than from your own blog
|
||||
- **No structured data** — Schema markup gives AI systems structured context about your content
|
||||
- **Keyword stuffing** — Unlike traditional SEO where it's just ineffective, keyword stuffing actively reduces AI visibility by 10% (Princeton GEO study)
|
||||
- **Blocking AI bots** — If GPTBot, PerplexityBot, or ClaudeBot are blocked in robots.txt, those platforms can't cite you
|
||||
- **Generic content without data** — "We're the best" won't get cited. "Our customers see 3x improvement in [metric]" will
|
||||
- **Forgetting to monitor** — You can't improve what you don't measure. Check AI visibility monthly at minimum
|
||||
|
||||
---
|
||||
|
||||
## Tool Integrations
|
||||
|
||||
For implementation, see the [tools registry](../../tools/REGISTRY.md).
|
||||
|
||||
| Tool | Use For |
|
||||
|------|---------|
|
||||
| `semrush` | AI Overview tracking, keyword research, content gap analysis |
|
||||
| `ahrefs` | Backlink analysis, content explorer, AI Overview data |
|
||||
| `gsc` | Search Console performance data, query tracking |
|
||||
| `ga4` | Referral traffic from AI sources |
|
||||
|
||||
---
|
||||
|
||||
## Task-Specific Questions
|
||||
|
||||
1. What are your top 10-20 most important queries?
|
||||
2. Have you checked if AI answers exist for those queries today?
|
||||
3. Do you have structured data (schema markup) on your site?
|
||||
4. What content types do you publish? (Blog, docs, comparisons, etc.)
|
||||
5. Are competitors being cited by AI where you're not?
|
||||
6. Do you have a Wikipedia page or presence on review sites?
|
||||
|
||||
---
|
||||
|
||||
## Related Skills
|
||||
|
||||
- **seo-audit**: For traditional technical and on-page SEO audits
|
||||
- **schema-markup**: For implementing structured data that helps AI understand your content
|
||||
- **content-strategy**: For planning what content to create
|
||||
- **competitor-alternatives**: For building comparison pages that get cited
|
||||
- **programmatic-seo**: For building SEO pages at scale
|
||||
- **copywriting**: For writing content that's both human-readable and AI-extractable
|
||||
152
skills/ai-seo/references/platform-ranking-factors.md
Normal file
152
skills/ai-seo/references/platform-ranking-factors.md
Normal file
|
|
@ -0,0 +1,152 @@
|
|||
# How Each AI Platform Picks Sources
|
||||
|
||||
Each AI search platform has its own search index, ranking logic, and content preferences. This guide covers what matters for getting cited on each one.
|
||||
|
||||
Sources cited throughout: Princeton GEO study (KDD 2024), SE Ranking domain authority study, ZipTie content-answer fit analysis.
|
||||
|
||||
---
|
||||
|
||||
## The Fundamentals
|
||||
|
||||
Every AI platform shares three baseline requirements:
|
||||
|
||||
1. **Your content must be in their index** — Each platform uses a different search backend (Google, Bing, Brave, or their own). If you're not indexed, you can't be cited.
|
||||
2. **Your content must be crawlable** — AI bots need access via robots.txt. Block the bot, lose the citation.
|
||||
3. **Your content must be extractable** — AI systems pull passages, not pages. Clear structure and self-contained paragraphs win.
|
||||
|
||||
Beyond these basics, each platform weights different signals. Here's what matters and where.
|
||||
|
||||
---
|
||||
|
||||
## Google AI Overviews
|
||||
|
||||
Google AI Overviews pull from Google's own index and lean heavily on E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness). They appear in roughly 45% of Google searches.
|
||||
|
||||
**What makes Google AI Overviews different:** They already have your traditional SEO signals — backlinks, page authority, topical relevance. The additional AI layer adds a preference for content with cited sources and structured data. Research shows that including authoritative citations in your content correlates with a 132% visibility boost, and writing with an authoritative (not salesy) tone adds another 89%.
|
||||
|
||||
**Importantly, AI Overviews don't just recycle the traditional Top 10.** Only about 15% of AI Overview sources overlap with conventional organic results. Pages that wouldn't crack page 1 in traditional search can still get cited if they have strong structured data and clear, extractable answers.
|
||||
|
||||
**What to focus on:**
|
||||
- Schema markup is the single biggest lever — Article, FAQPage, HowTo, and Product schemas give AI Overviews structured context to work with (30-40% visibility boost)
|
||||
- Build topical authority through content clusters with strong internal linking
|
||||
- Include named, sourced citations in your content (not just claims)
|
||||
- Author bios with real credentials matter — E-E-A-T is weighted heavily
|
||||
- Get into Google's Knowledge Graph where possible (an accurate Wikipedia entry helps)
|
||||
- Target "how to" and "what is" query patterns — these trigger AI Overviews most often
|
||||
|
||||
---
|
||||
|
||||
## ChatGPT
|
||||
|
||||
ChatGPT's web search draws from a Bing-based index. It combines this with its training knowledge to generate answers, then cites the web sources it relied on.
|
||||
|
||||
**What makes ChatGPT different:** Domain authority matters more here than on other AI platforms. An SE Ranking analysis of 129,000 domains found that authority and credibility signals account for roughly 40% of what determines citation, with content quality at about 35% and platform trust at 25%. Sites with very high referring domain counts (350K+) average 8.4 citations per response, while sites with slightly lower trust scores (91-96 vs 97-100) drop from 8.4 to 6 citations.
|
||||
|
||||
**Freshness is a major differentiator.** Content updated within the last 30 days gets cited about 3.2x more often than older content. ChatGPT clearly favors recent information.
|
||||
|
||||
**The most important signal is content-answer fit** — a ZipTie analysis of 400,000 pages found that how well your content's style and structure matches ChatGPT's own response format accounts for about 55% of citation likelihood. This is far more important than domain authority (12%) or on-page structure (14%) alone. Write the way ChatGPT would answer the question, and you're more likely to be the source it cites.
|
||||
|
||||
**Where ChatGPT looks beyond your site:** Wikipedia accounts for 7.8% of all ChatGPT citations, Reddit for 1.8%, and Forbes for 1.1%. Brand official sites are cited frequently but third-party mentions carry significant weight.
|
||||
|
||||
**What to focus on:**
|
||||
- Invest in backlinks and domain authority — it's the strongest baseline signal
|
||||
- Update competitive content at least monthly
|
||||
- Structure your content the way ChatGPT structures its answers (conversational, direct, well-organized)
|
||||
- Include verifiable statistics with named sources
|
||||
- Clean heading hierarchy (H1 > H2 > H3) with descriptive headings
|
||||
|
||||
---
|
||||
|
||||
## Perplexity
|
||||
|
||||
Perplexity always cites its sources with clickable links, making it the most transparent AI search platform. It combines its own index with Google's and runs results through multiple reranking passes — initial relevance retrieval, then traditional ranking factor scoring, then ML-based quality evaluation that can discard entire result sets if they don't meet quality thresholds.
|
||||
|
||||
**What makes Perplexity different:** It's the most "research-oriented" AI search engine, and its citation behavior reflects that. Perplexity maintains curated lists of authoritative domains (Amazon, GitHub, major academic sites) that get inherent ranking boosts. It uses a time-decay algorithm that evaluates new content quickly, giving fresh publishers a real shot at citation.
|
||||
|
||||
**Perplexity has unique content preferences:**
|
||||
- **FAQ Schema (JSON-LD)** — Pages with FAQ structured data get cited noticeably more often
|
||||
- **PDF documents** — Publicly accessible PDFs (whitepapers, research reports) are prioritized. If you have authoritative PDF content gated behind a form, consider making a version public.
|
||||
- **Publishing velocity** — How frequently you publish matters more than keyword targeting
|
||||
- **Self-contained paragraphs** — Perplexity prefers atomic, semantically complete paragraphs it can extract cleanly
|
||||
|
||||
**What to focus on:**
|
||||
- Allow PerplexityBot in robots.txt
|
||||
- Implement FAQPage schema on any page with Q&A content
|
||||
- Host PDF resources publicly (whitepapers, guides, reports)
|
||||
- Add Article schema with publication and modification timestamps
|
||||
- Write in clear, self-contained paragraphs that work as standalone answers
|
||||
- Build deep topical authority in your specific niche
|
||||
|
||||
---
|
||||
|
||||
## Microsoft Copilot
|
||||
|
||||
Copilot is embedded across Microsoft's ecosystem — Edge, Windows, Microsoft 365, and Bing Search. It relies entirely on Bing's index, so if Bing hasn't indexed your content, Copilot can't cite it.
|
||||
|
||||
**What makes Copilot different:** The Microsoft ecosystem connection creates unique optimization opportunities. Mentions and content on LinkedIn and GitHub provide ranking boosts that other platforms don't offer. Copilot also puts more weight on page speed — sub-2-second load times are a clear threshold.
|
||||
|
||||
**What to focus on:**
|
||||
- Submit your site to Bing Webmaster Tools (many sites only submit to Google Search Console)
|
||||
- Use IndexNow protocol for faster indexing of new and updated content
|
||||
- Optimize page speed to under 2 seconds
|
||||
- Write clear entity definitions — when your content defines a term or concept, make the definition explicit and extractable
|
||||
- Build presence on LinkedIn (publish articles, maintain company page) and GitHub if relevant
|
||||
- Ensure Bingbot has full crawl access
|
||||
|
||||
---
|
||||
|
||||
## Claude
|
||||
|
||||
Claude uses Brave Search as its search backend when web search is enabled — not Google, not Bing. This is a completely different index, which means your Brave Search visibility directly determines whether Claude can find and cite you.
|
||||
|
||||
**What makes Claude different:** Claude is extremely selective about what it cites. While it processes enormous amounts of content, its citation rate is very low — it's looking for the most factually accurate, well-sourced content on a given topic. Data-rich content with specific numbers and clear attribution performs significantly better than general-purpose content.
|
||||
|
||||
**What to focus on:**
|
||||
- Verify your content appears in Brave Search results (search for your brand and key terms at search.brave.com)
|
||||
- Allow ClaudeBot and anthropic-ai user agents in robots.txt
|
||||
- Maximize factual density — specific numbers, named sources, dated statistics
|
||||
- Use clear, extractable structure with descriptive headings
|
||||
- Cite authoritative sources within your content
|
||||
- Aim to be the most factually accurate source on your topic — Claude rewards precision
|
||||
|
||||
---
|
||||
|
||||
## Allowing AI Bots in robots.txt
|
||||
|
||||
If your robots.txt blocks an AI bot, that platform can't cite your content. Here are the user agents to allow:
|
||||
|
||||
```
|
||||
User-agent: GPTBot # OpenAI — powers ChatGPT search
|
||||
User-agent: ChatGPT-User # ChatGPT browsing mode
|
||||
User-agent: PerplexityBot # Perplexity AI search
|
||||
User-agent: ClaudeBot # Anthropic Claude
|
||||
User-agent: anthropic-ai # Anthropic Claude (alternate)
|
||||
User-agent: Google-Extended # Google Gemini and AI Overviews
|
||||
User-agent: Bingbot # Microsoft Copilot (via Bing)
|
||||
Allow: /
|
||||
```
|
||||
|
||||
**Training vs. search:** Some AI bots are used for both model training and search citation. If you want to be cited but don't want your content used for training, your options are limited — GPTBot handles both for OpenAI. However, you can safely block **CCBot** (Common Crawl) without affecting any AI search citations, since it's only used for training dataset collection.
|
||||
|
||||
---
|
||||
|
||||
## Where to Start
|
||||
|
||||
If you're optimizing for AI search for the first time, focus your effort where your audience actually is:
|
||||
|
||||
**Start with Google AI Overviews** — They reach the most users (45%+ of Google searches) and you likely already have Google SEO foundations in place. Add schema markup, include cited sources in your content, and strengthen E-E-A-T signals.
|
||||
|
||||
**Then address ChatGPT** — It's the most-used standalone AI search tool for tech and business audiences. Focus on freshness (update content monthly), domain authority, and matching your content structure to how ChatGPT formats its responses.
|
||||
|
||||
**Then expand to Perplexity** — Especially valuable if your audience includes researchers, early adopters, or tech professionals. Add FAQ schema, publish PDF resources, and write in clear, self-contained paragraphs.
|
||||
|
||||
**Copilot and Claude are lower priority** unless your audience skews enterprise/Microsoft (Copilot) or developer/analyst (Claude). But the fundamentals — structured content, cited sources, schema markup — help across all platforms.
|
||||
|
||||
**Actions that help everywhere:**
|
||||
1. Allow all AI bots in robots.txt
|
||||
2. Implement schema markup (FAQPage, Article, Organization at minimum)
|
||||
3. Include statistics with named sources in your content
|
||||
4. Update content regularly — monthly for competitive topics
|
||||
5. Use clear heading structure (H1 > H2 > H3)
|
||||
6. Keep page load time under 2 seconds
|
||||
7. Add author bios with credentials
|
||||
|
|
@ -352,6 +352,7 @@ Visual or structured representation of how content interconnects.
|
|||
|
||||
- **copywriting**: For writing individual content pieces
|
||||
- **seo-audit**: For technical SEO and on-page optimization
|
||||
- **ai-seo**: For optimizing content for AI search engines and getting cited by LLMs
|
||||
- **programmatic-seo**: For scaled content generation
|
||||
- **email-sequence**: For email-based content
|
||||
- **social-content**: For social media content
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
---
|
||||
name: paid-ads
|
||||
description: "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,' 'ad copy,' 'ad creative,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' or 'audience targeting.' This skill covers campaign strategy, ad creation, audience targeting, and optimization."
|
||||
description: "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,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' or 'audience targeting.' This skill covers campaign strategy, audience targeting, and optimization. For bulk ad creative generation and iteration, see ad-creative."
|
||||
metadata:
|
||||
version: 1.0.0
|
||||
---
|
||||
|
|
@ -308,6 +308,7 @@ For tracking, see also: [ga4.md](../../tools/integrations/ga4.md), [segment.md](
|
|||
|
||||
## Related Skills
|
||||
|
||||
- **ad-creative**: For generating and iterating ad headlines, descriptions, and creative at scale
|
||||
- **copywriting**: For landing page copy that converts ad traffic
|
||||
- **analytics-tracking**: For proper conversion tracking setup
|
||||
- **ab-test-setup**: For landing page testing to improve ROAS
|
||||
|
|
|
|||
|
|
@ -174,4 +174,5 @@ You can combine multiple schema types on one page using `@graph`:
|
|||
## Related Skills
|
||||
|
||||
- **seo-audit**: For overall SEO including schema review
|
||||
- **ai-seo**: For AI search optimization (schema helps AI understand content)
|
||||
- **programmatic-seo**: For templated schema at scale
|
||||
|
|
|
|||
|
|
@ -368,7 +368,7 @@ Same format as above
|
|||
## References
|
||||
|
||||
- [AI Writing Detection](references/ai-writing-detection.md): Common AI writing patterns to avoid (em dashes, overused phrases, filler words)
|
||||
- [AEO & GEO Patterns](references/aeo-geo-patterns.md): Content patterns optimized for answer engines and AI citation
|
||||
- For AI search optimization (AEO, GEO, LLMO, AI Overviews), see the **ai-seo** skill
|
||||
|
||||
---
|
||||
|
||||
|
|
@ -404,6 +404,7 @@ Same format as above
|
|||
|
||||
## Related Skills
|
||||
|
||||
- **ai-seo**: For optimizing content for AI search engines (AEO, GEO, LLMO)
|
||||
- **programmatic-seo**: For building SEO pages at scale
|
||||
- **schema-markup**: For implementing structured data
|
||||
- **page-cro**: For optimizing pages for conversion (not just ranking)
|
||||
|
|
|
|||
Loading…
Reference in a new issue