og-image-generator

name

og-image-generator

description

Generate Open Graph images for social sharing previews across Facebook, LinkedIn, Slack, Discord, WhatsApp, Telegram, Pinterest, iMessage, and QQ. Use when the user mentions "OG image," "og:image," "Open Graph image," "social share image," "link preview image," "generate OG image," "dynamic og image," "social card image," "programmatic og," or "auto-generate social images." Core approaches: AI image generation (Nano Banana, GPT Image, Flux), Agent-native content-aware workflow with page priority (S/A/B/C), Satori+resvg pipeline, Puppeteer. Supports dual pipeline (Satori for layout styles, AI for texture styles, Hybrid for best quality). Covers 16 visual styles across 10 layout-type (Satori-native) and 6 texture-type (AI/hybrid). For Twitter-specific image generation, use twitter-card-image-generator.

OG Image Generator

Generate Open Graph images — the 1200x630px preview cards that appear when links are shared on social platforms. Pages with unique, well-designed OG images get 2–3x more clicks than bare URL links.

This skill's core is content-aware generation: extracting meaning from the page, matching a visual style, and producing an image that reflects the actual content — not just filling a template with a title.

When to Use

• User needs 1200×630px (1.91:1) images for Facebook, LinkedIn, Slack, Discord, WhatsApp, Telegram, Pinterest, iMessage, or QQ
• User mentions og:image, Open Graph, social share image, link preview image, or dynamic/programmatic OG generation
• User wants Satori JSX templates, AI image generation, or a content-aware workflow that extracts page meaning into a visual card
• User needs one of the six visual styles (Terminal, Magazine, Swiss, Pixel, Brutalist, Newspaper)

When NOT to Use

• Twitter/X Card images (1200×675, 2:1) — use twitter-card-image-generator instead
• Only setting HTML meta tags (not creating the image file) — use open-graph from marketing-skills
• No-code visual editor or hosted API — use Oginify instead of running an agent pipeline

When invoking: On first use, open with 1–2 sentences on what this skill covers and why it matters, then go directly to the generation approach that best fits the user's needs. On subsequent use or when the user asks to skip, go directly to the main output.

1. Six Generation Approaches

These are six fundamentally different ways to produce an OG image. They answer "how does an image get made?" — orthogonal to "what does the image look like?" (which §3 Style System answers).

1.1 AI Image Generation (Core #1)

Use an external AI image model to generate the OG image directly from a prompt. This is the most flexible approach — no template code, no font files, no layout engine. The model handles composition, color, and visual hierarchy in one shot.

When this is the right choice: Visual-first pages where the image's aesthetic matters more than exact text — game pages, design portfolios, brand launches, lifestyle content, event announcements. Also good for pages that need a highly specific visual mood that's hard to encode in code-based templates.

When it's NOT: When the OG image must contain precise, error-free text (product names, technical terms, Chinese characters). AI models struggle with text rendering — misspellings, garbled characters, or missing words are common.

Tools and their strengths:

Tool	Text accuracy	Aesthetic quality	Speed	Chinese text	Best for
GPT Image 2.0 (GPT-4o image)	Highest	High	5–15s	Moderate	Text-heavy OG, complex layouts, multimodal understanding
Flux (Black Forest Labs)	Moderate	Highest	3–8s (API)	Weak	Visual quality priority, open-source flexibility
Nano Banana	Low	Good	2–5s	Weak	Fast iteration, budget-friendly, simple compositions
DALL-E 3	Moderate	High	5–10s	Weak	Photorealistic scenes, illustration style
Midjourney	N/A (no API)	Highest	30–60s	N/A	Inspiration, one-off high-quality images

Prompt strategy for OG images: Three-part structure:

Part 1 — Visual description: background, composition, mood, lighting
Part 2 — Text specification: EXACT text to display, in quotes, with font size hints
Part 3 — Technical constraints: "1200x630px, clean legible text, no edge clutter"

Example:

A dark navy gradient background with subtle grid lines. A bold white title reads "Best AI Image Generators 2026" centered at 60pt. Small label "alignify.co" in bottom-right corner. Clean, modern, minimal. 1200x630px social card. No decorative elements near edges.

The hybrid approach (recommended): AI generates the background/atmosphere; code-based rendering (Satori, §1.3) overlays the text. This gives you AI's visual quality + code's text precision. Especially important for Chinese text where AI models still struggle.

1.2 Agent-Native Content-Aware Workflow v3 (Core #2)

This is not a rendering technology — it's a 9-step decision-making workflow. The Agent classifies the page, determines priority (S/A/B/C), matches style using a 3D matrix, selects the right pipeline, and drives generation end-to-end.

PHASE 1 — Classify & Decide (NEW in v3)

1. CLASSIFY THE PAGE
   → Determine page type from URL pattern + content signals:
     /blog/*, /post/* → blog_post
     /pricing → pricing
     /docs/* → docs
     (Full taxonomy: references/content-strategy.md — 100+ types in 13 categories)
   
   → Detect site type:
     Has pricing/feature/SaaS → SaaS
     Has product grid/cart → eCommerce
     Has byline/reading time → Content/Media
     (Full taxonomy: references/content-strategy.md — 35 types)

2. DETERMINE PRIORITY (NEW)
   → Query content-strategy.md S/A/B/C table:
     S (Must-do): blog_post, changelog, research_report, campaign_landing...
     A (High): homepage, pricing, feature_page, comparison, event_page...
     B (Medium): about, docs, author_page, category, integration...
     C (Skip): login, cart, checkout, dashboard, privacy, terms, 404, contact...
   
   → IF C-level: STOP. Report "This page type rarely gets shared. Use one brand-default
     1200×630 image instead. Proceed anyway? [y/N]"
   → IF B-level: If >5 B pages → template batch strategy. If ≤5 → treat as A.
   → IF A/S-level: Continue to full workflow.

3. EXTRACT CONTENT WITH CONTEXT (enhanced)
   → Extract: title (1-2 lines), subtitle, THE ONE most interesting data point,
     date, author, category tags, hero image URL, brand colors, content tone
     (technical/narrative/data_heavy/playful/urgent/premium/raw)
   → Output: ContentProfile { title, subtitle, dataPoint, meta, visualCandidates, tone }

PHASE 2 — Match Style & Build Recipe (enhanced)

4. MATCH STYLE (3D multi-axis, replacing old tone-only mapping)
   → Call selectStyle(pageType, siteType, contentTone)
     Algorithm in references/style-system-v3.md §Style Selection Algorithm
   → Uses 16×100 page-type matrix + 16×35 site-type matrix
   → Output: { primary, variants[2-3], avoid[] }
   
   Example: SaaS pricing page → Swiss Minimal (score:7), Neo-Swiss Gradient (5), Bento Grid (4)
            Avoid: Grunge, Vaporwave, Pixel Retro

5. BUILD VISUAL RECIPE (NEW)
   → For the selected (style, pageType) combo, query style-system-v3.md:
     - Required elements (must_include)
     - Recommended elements (adds value)
     - Forbidden patterns (style-breaking)
     - Layout wireframe (ASCII)
     - Color preset
     - Font config
     - Agent check checklist
   → Output: VisualRecipe

6. SELECT PIPELINE (NEW — dual pipeline decision)
   → Satori pipeline (layout styles #1-10): zero cost, instant, text-perfect
   → AI pipeline (texture styles #11-16): ~$0.067/img, 5-15s, visual quality
   → Hybrid (AI bg + Satori text): best quality + perfect text accuracy
   → Decision tree: references/pipeline-guide.md

PHASE 3 — Generate & Validate

7. GENERATE
   → If Satori: copy seed template from templates/{style}.tsx, fill with ContentProfile
   → If AI: build prompt from VisualRecipe.aiPromptTemplate, call AI model
   → If Hybrid: AI generates background → Satori overlays text from ContentProfile

8. VALIDATE (enhanced)
   → Run pre_flight checks (§9): page classification, priority, pipeline choice
   → Run style-specific checks from VisualRecipe.agentChecks
   → Run standard Agent YAML checks (§9)

9. SUGGEST NEXT ACTIONS (NEW)
   → If ≥2 variants generated: "These styles differ enough for A/B testing"
   → If S-level page: "Consider regenerating when content updates"
   → Deployment path: WordPress(Featured Image), Next.js(opengraph-image.png), etc.

1.3 Satori + resvg (Code-based generation)

The most widely adopted code-based approach. JSX → Satori → SVG → resvg → PNG. Edge-compatible, 100–500ms render time.

When to use: Text must be pixel-perfect. Works on Next.js, Cloudflare Workers, Vercel Edge, any JS runtime.

Quick implementation (Next.js App Router):

// app/og/route.tsx
import { ImageResponse } from 'next/og';

export const runtime = 'edge';

export async function GET(req: Request) {
  const { searchParams } = new URL(req.url);
  const title = searchParams.get('title') ?? 'Default Title';

  return new ImageResponse(
    (
      <div style={{
        width: '100%', height: '100%',
        display: 'flex', flexDirection: 'column',
        alignItems: 'flex-start', justifyContent: 'flex-end',
        background: 'linear-gradient(135deg, #0f172a, #1e293b)',
        color: '#f8fafc', fontFamily: 'Inter',
        padding: '80px 100px',
      }}>
        
        {title}
        yoursite.com
      
    ),
    { : , :  },
  );
}

For Satori CSS limitations, see references/satori-constraints.md.

1.4 Puppeteer / Playwright

Headless browser screenshot. Full CSS, JavaScript, Canvas, WebGL. 1–3s render, ~300MB Chromium binary. Cannot run on Edge.

When to use: CSS Grid layouts, Canvas charts, WebGL backgrounds, complex CJK font shaping.

import puppeteer from 'puppeteer';

async function generateOgImage(html: string): Promise<Buffer> {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();
  await page.setViewport({ width: 1200, height: 630 });
  await page.setContent(html);
  const screenshot = await page.screenshot({ type: 'png' });
  await browser.close();
  return Buffer.from(screenshot);
}

1.5 Managed Services

API-based, no rendering pipeline to maintain:

Service	Best for
OG Kit	Visual template editor, non-developers
Cloudinary	Already using Cloudinary for images
Vercel OG	Already on Vercel, wraps Satori
imgix	Enterprise, URL-based image manipulation

1.6 JSON Config (declarative)

Define OG images as JSON. @zyrab/domo-og is the leading library — WASM-powered, edge-compatible.

{
  "width": 1200, "height": 630,
  "background": "#1a1a2e",
  "elements": [
    { "type": "text", "content": "{{title}}", "fontSize": 60, "color": "#fff" }
  ]
}

When to use: OG config lives in a CMS, non-developers maintain, simple text-only templates.

1.7 Page Priority Decision (NEW in v3)

The FIRST question is not "what style?" but "should I generate at all?"

Decision flow:

Classify page type (100+ types, see content-strategy.md §2)
  → S-level: blog_post, changelog, research_report, campaign_landing, newsletter_issue...
  → A-level: homepage, pricing, feature_page, comparison, event_page, product_detail, waitlist...
  → B-level: about, docs, author_page, category, integration, template, tutorial, podcast...
  → C-level: login, signup, cart, checkout, dashboard, billing, privacy, terms, 404, contact...

IF C-level → STOP. Suggest one brand-default 1200×630 image for entire site.
IF B-level AND site has >5 B pages → recommend template batch strategy.
IF A/S-level → proceed with full content-aware workflow (§1.2).

Platform built-in OG check: Before generating, verify the user's platform doesn't already auto-generate adequate OG images. Platforms with built-in OG: Vercel, Next.js (ImageResponse), WordPress (Jetpack), Ghost, Substack, Medium, GitHub, Framer, Webflow, Notion, Dev.to, Hashnode. If the platform's built-in OG is good enough → skip. If not → generate.

Site-type priority modifier: Content/Media, News, DevTool, Personal/Portfolio sites → boost all B-level pages to A (their traffic relies on social sharing). Healthcare, Government, FinTech → suppress aggressive styles.

See references/content-strategy.md for the full priority framework.

1.8 Pipeline Selection (NEW in v3)

Two rendering pipelines, chosen based on the selected style:

Pipeline	Styles	Speed	Cost	Text Accuracy	Best For
Satori	#1-10 (layout styles)	100-500ms	$0	100% perfect	Swiss, Terminal, Brutalist, Neo-Brutalism, Bento, Newspaper...
AI	#11-16 (texture styles)	5-15s	~$0.067/img	~80-95%	Text Overlay, Cinematic, Collage, Risograph, Vaporwave, Grunge
Hybrid	#11-16 recommended	5-15s	~$0.067/img	100% perfect	AI generates background/texture → Satori overlays pixel-perfect text

Decision rule: See references/pipeline-guide.md for the complete decision tree, AI prompt templates per style, and hybrid implementation patterns.

Hybrid is the default recommendation for all texture styles (#11-16) when CJK text or product names must be exact. AI generates the atmosphere/photo/texture; Satori renders the text — combining AI's visual quality with code's text precision.

2. Typography

See references/typography.md for the complete OG image typography guide: font philosophy, pairing formulas, type scale (Perfect Fourth 1.333), weight assignments, CJK-specific rules, and line-length constraints.

Key constraints enforced across all styles:

• Minimum font size: 24px at 1200px canvas width
• Title: 56–128px depending on character count and style
• Body/secondary: 28–42px
• Labels/meta: 20–28px
• Chinese titles: ≤20 characters per line
• English titles: ≤15 words per line

3. Style System — 20 Visual Styles

See references/style-system-v3.md for the complete design system with 20 styles, pipeline compatibility, style×page-type matrix (20×100), and style×site-type matrix (20×35). The legacy references/style-system.md is retained for reference on original 6 styles.

Layout-Type Styles (Satori-Native, #1-10)

Zero-cost, instant rendering, 100% text accuracy.

#	Style	Template	Pipeline	Signature
1	Terminal / CLI	terminal.tsx	Satori	$> prompts, monospace, green-on-black
2	Magazine Editorial	magazine.tsx	Satori	Serif display, paper tones, pull quotes
3	Swiss Minimal	swiss.tsx	Satori	Inter light, single accent, left grid
4	Pixel Retro	pixel.tsx	Satori	Press Start 2P, 8-bit palette, HUD
5	Brutalist	brutalist.tsx	Satori	B&W, max-bold, zero radius
6	Newspaper	newspaper.tsx	Satori	Multi-column, serif titles, dateline
7	Neo-Brutalism	neo-brutalism.tsx	Satori	Clash colors, 6px borders, hard shadow
8	Bento Grid	bento-grid.tsx	Satori	Asymmetric cards, dark glow, 14px radius
9	Neo-Swiss Gradient	neo-swiss-gradient.tsx	Satori	Warm gradient, Inter 200, hairline rules
10	Dark Gradient+Texture	dark-gradient-texture.tsx	Satori	Radial glow, dot-grid, glowing line

Texture-Type Styles (AI/Hybrid, #11-16)

Require AI for full effect. Hybrid (AI bg + Satori text) recommended for text accuracy.

#	Style	Template	Pipeline	Signature
11	Text Overlay	text-overlay-hybrid.tsx	Hybrid	Photo bg + dark mask + bold white title
12	Cinematic	cinematic.tsx	AI+Hybrid	Film grading, bokeh, grain, lower-third title
13	Collage	collage.tsx	AI+Hybrid	Torn edges, tape, polaroids, layered panels
14	Risograph	risograph.tsx	AI+Hybrid	2-3 colors, halftone dots, ink offset
15	Vaporwave	vaporwave.tsx	AI+Hybrid	Neon sunset, statues, CRT scanlines, glitch
16	Grunge	grunge.tsx	AI-Native	Noise grain, photocopy texture, distressed

AI-Native Styles (#17-20 — Pure AI, No Satori)

These styles are AI-only: the model generates the complete image with text built in. No Satori template, no Hybrid step. One prompt, one image.

#	Style	Template	Pipeline	Signature
17	AI Painterly	ai-painterly.tsx	AI-Native	Watercolor/oil/ink — text is painted, not typeset
18	Abstract Gradient	abstract-gradient.tsx	AI-Native	Zero text. Pure color field. Rothko-esque
19	AI Sticker/Badge	ai-sticker.tsx	AI-Native	1-3 word badge floating on atmospheric bg
20	AI Infographic	ai-infographic.tsx	AI-Native	Editorial data art — visual comparisons, not precise charts

Style selection (used by Agent-Native workflow §1.2 step 4):

The Agent now uses a 3D matrix (page_type × site_type × content_tone) instead of simple tone-only mapping. The full algorithm is in references/style-system-v3.md §Style Selection Algorithm. Quick reference:

Content Tone	Top 3 Styles
Technical, data-heavy	Swiss, Dark Gradient, Terminal
Narrative, brand story	Magazine, Cinematic, Neo-Swiss Gradient
Dev tool, CLI, API	Terminal, Dark Gradient, Neo-Brutalism
Design-forward, bold	Neo-Brutalism, Brutalist, Collage
News, timely, dense	Newspaper, Text Overlay, Bento Grid
Playful, retro, indie	Pixel, Vaporwave, Collage
Premium, refined	Cinematic, Neo-Swiss Gradient, Magazine
Raw, anti-convention	Grunge, Risograph, Brutalist

4. Font Handling

Satori cannot read system fonts — every font must be explicitly loaded. See references/font-loading.md for loading strategies, CJK subsetting, and edge runtime limits.

const fonts = [
  { name: 'Inter', data: await loadFont('./Inter-Bold.ttf'), weight: 700 },
  { name: 'Inter', data: await loadFont('./Inter-Regular.ttf'), weight: 400 },
];

next/og bundles Geist Sans + Geist Mono automatically — no manual loading for Latin text in Next.js.

5. Caching Strategy

Content-addressed cache key: hash(title + style + options) → immutable cache.

res.headers.set('Cache-Control', 'public, max-age=604800, immutable');

Vercel: 30-day default. Other platforms: set explicitly. For AI-generated images, cache serves same prompt → same image, avoiding re-generation costs.

6. Static Fallback

Every page must have a static fallback. Next.js auto-detects opengraph-image.png in the app directory.

images: [
  { url: `/og?title=${title}`, width: 1200, height: 630 },
  { url: '/opengraph-image.png', width: 1200, height: 630 },
],

7. Framework Implementations

• Next.js (App Router): next/og ImageResponse, route at app/og/route.tsx
• Nuxt: nuxt-og-image module, Satori-powered
• Astro: @astrojs/og or manual Satori + sharp
• SvelteKit: Manual Satori in +server.ts endpoint
• Cloudflare Workers: workers-og or Satori + resvg-wasm
• Generic Node.js: Build-time batch script

8. Common Pitfalls

1. AI text hallucination: AI-generated images may garble or misspell text. Always validate. For critical text, use the hybrid approach (AI background + Satori text overlay).
2. Missing width/height on flex containers: Satori requires explicit dimensions.
3. CSS Grid or gap: Not supported by Satori. Use margin/padding.
4. No auto text wrapping in Satori: Split long titles manually.
5. WASM no background images: @resvg/resvg-wasm can't load external images.
6. Font weight mismatch: Load the exact weight you reference.
7. CJK characters missing: Geist/Inter don't include CJK — load a CJK font.
8. Relative image URLs: Must be absolute https:// for external platforms.
9. Over-compression: Don't quality=60 text-heavy OG images.
10. No cache strategy: Re-rendering every request wastes compute.
11. Generic OG for every page: The #1 missed opportunity. Use the Agent-native workflow (§1.2).

9. Agent YAML Checks

pre_flight:  # NEW in v3 — run before generation
  - id: page-classification
    description: Page type identified from URL pattern + content signals (content-strategy.md §2)
  - id: priority-determination
    description: S/A/B/C level assigned. C-level pages should NOT use custom generation.
  - id: site-type-detection
    description: Site type inferred from content, title patterns, and business signals
  - id: c-level-gate
    description: If C-level, agent has warned user and confirmed  
    
              
    
          


  
    
          
    
                
    
             
    
           

  
    
         
    
               
    
                 
    
               
    
                
    
               

  
    
              
    
             
    
                

10. Related Skills

These skills are optional — this skill works standalone. Install them if you need additional capabilities:

Same repo (always installed together):

• twitter-card-image-generator: X/Twitter image generation — same 6 styles, 1200×675px, platform-specific adaptations

Separate repos (may or may not be installed):

• open-graph (marketing-skills): HTML meta tag configuration for og:title, og:image, og:url, etc. Handles how to SET the image URL; this skill handles how to CREATE the image.
• twitter-cards (marketing-skills): HTML meta tag configuration for twitter:card, twitter:site, twitter:image, fallback logic
• social-share-generator (marketing-skills): Share button UI that consumes OG/Twitter Card data
• page-metadata (marketing-skills): Hreflang, meta robots, other meta tags