Render a 'search-grid' (Pinterest search-moodboard) video from a config — a real-DOM page with four continuous beats (masonry search grid + typing hook with counter-drift columns → 3 cards slide in from the right and stack → the top card box-grows to fullscreen then swipe-left ×2 through captioned feature shots → warm end card), frame-stepped via Chromium and encoded with FFmpeg — deterministic assembly, FREE (real brand photos + logo; the optional music bed comes from create-music-elevenlabs), so type/logo/photos stay pixel-crisp. Use for the search-grid format.
npx skills add https://github.com/gooseworks-ai/goose-skills --skill render-search-grid
Render the 'search-grid' format from a config. It is a deterministic assembler — no
generative image/video, no AI-rendered text. Everything on screen is the brand's REAL
product/lifestyle photography + logo, so the typed hook, feature captions, wordmark, and
photos stay pixel-crisp. The only paid input is an optional music bed, produced upstream
by create-music-elevenlabs and passed to render.py --music.
search bar; a believable phrase types in letter-by-letter. Side columns drift DOWN, the
middle column drifts UP (counter-parallax).
blurred backdrop.
stacked rect to full-screen, animating width/height — NOT transform:scale, which would
stretch the image), then swipe-left → swipe-left through the SAME 3 rooms, each now
full-bleed with a caption. The 3 cards ARE the 3 features.
scripts/build_html.py --config config.json --out index.html — config → a singleself-contained HTML page exposing window.seek(tMs) (images base64-embedded).
scripts/capture.js --html index.html --out frames --fps 30 --duration 18000 — headlessChromium frame-steps seek() to a PNG per frame (auto-discovers a cached Playwright
chromium, or pass --exe).
scripts/render.py --config config.json [--music bed.m4a] --out master.mp4 — orchestratesbuild → capture → FFmpeg (muxes the bed with -map 0:v:0 -map 1:a:0 when --music is
given; $0 silent pass without it).
scripts/prep_assets.py crop in.jpg out.jpg / logo logo.jpg wordmark.png — the twofixes this format needs almost every time: crop baked-in white L/R margins off heroes, and
key the white out of a black-on-white logo JPG to a transparent PNG.
See scripts/config.example.json for the full config shape (a real worked example).
canvas, hook, grid_cols (3 columns × 6 distinct tiles), rooms (exactly 3
{image, caption} — the cards AND the features), stack_bg (blurred warm backdrop),
endcard (hero, wordmark, tagline, cta, bg). Craft rules the renderer assumes the
inputs already honor: real brand assets only; 6 distinct tiles/column so the drift never
repeats; warm (never near-white) backdrops; cropped hero margins; transparent-bg wordmark;
captions/tagline/CTA are the brand's OWN approved copy (no invented claims).
node + playwright-core (or a cached Playwright chromium) and ffmpeg on PATH; python3
with Pillow (for prep_assets.py).
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This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Take gooseworks-ai/render-search-grid from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.