create-image-fal
Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent. image_urls…
Render a 'mosaic-grid-reveal' video from a config — a real-DOM FULL-BLEED N×N mosaic of real product tiles that pops in one tile at a time (scatter order, ease-out-back overshoot), the grid clears, then the brand wordmark builds line-by-line followed by a sub-label, tagline, and
$ npx -y skills add gooseworks-ai/goose-skills --skill render-mosaic-grid-reveal --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/render-mosaic-grid-revealContext preview
The summary Claude sees to decide when to auto-load this skill.
Render a 'mosaic-grid-reveal' video from a config — a real-DOM FULL-BLEED N×N mosaic of real product tiles that pops in one tile at a time (scatter order, ease-out-back overshoot), the grid clears, then the brand wordmark builds line-by-line followed by a sub-label, tagline, and
name: render-mosaic-grid-reveal description: Render a 'mosaic-grid-reveal' video from a config — a real-DOM FULL-BLEED N×N mosaic of real product tiles that pops in one tile at a time (scatter order, ease-out-back overshoot), the grid clears, then the brand wordmark builds line-by-line followed by a sub-label, tagline, and CTA; frame-stepped via Playwright and encoded with FFmpeg — deterministic assembly, FREE (the music bed comes from create-music-elevenlabs), so the wordmark, tile captions, and CTA stay pixel-crisp. Use for the mosaic-grid-reveal format. status: active
Render the `mosaic-grid-reveal` format from a config. The signature of this format is a **full-bleed N×N mosaic** (default 3×3) of the brand's real product stills that **pops in one tile at a time** (scatter order, ease-out-back "pop"), building the whole grid; the grid then **clears** (scale-up + fade) and a clean end card **builds line-by-line** — the brand's real wordmark, then a small sub-label, then the tagline, then a CTA. Silent by design (a light music bed is muxed separately via `create-music-elevenlabs`). The hook is RANGE — nine maximally-distinct variants show how much choice the brand offers.
Everything is a real-DOM HTML scene **frame-stepped** to PNG via Playwright and encoded with FFmpeg, so the wordmark, tile captions, and CTA stay **pixel-crisp** (a video model would smear them). No generative video, no i2v, no AI-rendered text. This capability is **FREE and deterministic** — the only paid step of the format (the music bed) is a separate media cap.
recolored via `palette.ink`. Never AI-render it. `wordmark_viewbox`, `wordmark_width` tune it.
`name` (caption), `bg` (soft pastel echoing the variant), `ink` (deep caption color).
`scripts/config.example.json` is a filled example (the Pair Eyewear "RANGE" worked example); the tile `image`/`wordmark` paths are brand inputs bound by the orchestrator at remix time.
python3 scripts/build_html.py --config config.json --out hyperframe.html # emits scene, writes duration_sec back python3 scripts/render.py --config config.json --html hyperframe.html --out master-silent.mp4
`build_html.py` computes the full timeline and writes `duration_sec` back into the config so `render.py` (which reads dims/fps/duration from the config) frame-steps `window.renderAt(t)` at `fps` and FFmpeg-encodes the silent master. Then mux the `create-music-elevenlabs` bed: `ffmpeg -i master-silent.mp4 -i bed.wav -map 0:v:0 -map 1:a:0 -c:v copy -c:a aac -shortest out.mp4`.
empty margin. Tiles pop in one at a time (scatter order), never all-at-once or static.
prices, or shipping speed.
Put your AI agent on the growth team. Research customers and competitors, analyze what is working, create the next campaign, and learn from the result.
Repo: gooseworks-ai/goose-skills
Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent. image_urls…
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Scrape competitor ads from Google Ads by domain. Returns ad creatives, formats, and campaign details. Use for competitive ad research and messaging analysis.