Vercel Style OG Image: Image Skill for Claude Code

A white dot-grid page with the centered stacked words Develop. Preview. Ship., the last in a coral-to-amber gradient, and the small black Vercel triangle at the lower right

A white dot-grid page with the stacked words Code. Merge. Live. at the left of center, the last in a coral-to-amber gradient, the small name Pushvale below and a coral dot at the lower right

Runs in

Install guides

Claude Code Cursor

Generates with

Host Agent LLM

Uses tools

FAL

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What you get

One 16:9 WebP card with stacked heavy words on a dot grid, your brand and headline exact
The exact prompt it sent plus the saved FAL task file; rerunning resumes that request rather than buying a new one
A review of spelling, the 6% safe margin and the 16:9 frame before the card reaches you

Good fit

Developer tools and launch posts
Three-word action lines
Brands that would rather lead with type

Not for

Photos, people or interfaces
Anything that needs full sentences
Copying a logo that exists

Social mediaProduct launchMake an OG imageog imagesocial carddeveloper toolsbig typeminimal

Good forMake an OG image

About this Skill

You say/ours-vercel-style-og Brand: Shipyard Labs, an edge database for small teams. Headline: "Query. Cache. Scale." Make the share card.

If you want a developer-launch OG image from your Fable 5 agent with nothing on it but words, this is the one. A faint gray dot grid covers the white page. Stacked line over line with tight spacing, two or three short words are set in a very bold black sans-serif, and the last word is filled with a warm coral-to-amber gradient. Off to one side sits a single small solid black shape: a triangle, a diamond or a dot. Words and accent are settled with your brand in mind, GPT Image 2 on FAL renders the 16:9 WebP, and each letter is checked before handover.

How it works

Agree on the name, one headline and one picture idea; drop anything that blurs at thumbnail size
Lay out the card from references/visual-system.md and fit your colors to its four style anchors
Strip out outside names, marks, faces, screens and slogans, then invent the accent shape for your brand
Write a prompt about visible things only: frame, layout, light, palette, subject and type position
Send one request with the bundled FAL helper and keep the task file it writes
Read each letter, check the 6% margins and the 16:9 frame, and only then run validate-output.mjs
If a flaw remains, propose one prompt change and wait for your OK before a second paid request

Checked before delivery

validate-output.mjs passes with --require-format webp --require-16-9, and the prompt file has no emoji, arrows or symbol characters
Brand and headline read correctly letter by letter, with key text and faces inside a 6% margin on every side
Every source name, logo, slogan, person, interface and watermark is replaced by the user's own identity or a new one, and the layout is new for this subject
Exactly one paid request per approved generation

What you need before you start

You bring: Brand or project name, spelled as it should appear on the card · One short headline · What the page, product or audience is · Optional: brand colors, a logo the user may use, a mood, owned reference images, a platform safe zone
Dependencies: Node.js 20+ to run the included FAL script · Your own FAL API key, set as FAL_KEY; FAL charges for each image
Outside costs: FAL_KEY
Last tested: v0.1.1 — Claude Code / Codex / Cursor

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FAQ

Does the gradient word have to be coral and amber?

Not necessarily. Your brand colors are mapped onto the four style anchors, one of which is that coral-to-amber word, and kept where they fit. The words, the shape and any logo you may use belong to your brand.

Can it work from an image I already have?

If the image is yours or you may use it, yes. Hand it over with --reference and GPT Image 2 runs in edit mode instead. Only mood, color and layout are taken from the picture; nothing in it is reproduced on the card.

Is there a cost beyond the Skill?

Yes: FAL bills every image to your own account. The helper never retries by itself, and running the same command again only picks up the saved request, so checking on a slow job never pays for a second one.

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