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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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.
config.json)width, height, fps — canvas + frame rate (default 1080×1920, 30).wordmark — brand logo SVG (full <svg> or bare <path> markup) or PNG path. Real DOM,
recolored via palette.ink. Never AI-render it. wordmark_viewbox, wordmark_width tune it.palette — bg (page colour; the demo used a warm off-white), accent + accent_deep (brand color), ink, cap.grid — cols/rows (default 3×3), inset (outer margin), gap.tiles — one per cell (length must equal cols*rows): image (real variant still),
name (caption), bg (tile colour, from choices.tile_look — the demo used a soft pastel echoing each variant), ink (deep caption color).pop_order — scatter order across cells (default corners → center → edges).timing — grid_in0, cadence, pop, hold, clear (seconds).end_card — sub, tagline_top, tagline_bottom (bold), cta, url. Brand's own approved copy only.eyebrow — optional top kicker held during the grid.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.
Its tiles, tile colours, end-card copy and music prompt are Pair's answers, not defaults.
The recipe asks the user these before any paid step; the renderer draws whatever the config says.
range — which 9 products/variants fill the grid → tiles[].image, tiles[].name. Asked of the user; the demo used 9 eyewear colourways.tile_look — tile backgrounds → tiles[].bg, tiles[].ink, palette.bg. Asked of the user; the demo used a soft pastel per variant.music — the bed's genre/mood → music.prompt (consumed by create-music-elevenlabs). Asked of the user; the demo used light upbeat marimba.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.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.
日本語の概要は準備中です。原文の説明を表示しています。
For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.
日本語の概要は準備中です。原文の説明を表示しています。
The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.
日本語の概要は準備中です。原文の説明を表示しています。
Turn a brand's facts, a campaign brief and the product into a one-minute Meta ad strategy with its reasoning — goal, audience, objective and placements, budget split, how many ads and how different they must be (generate 3x so the user can choose), the test frame, the success metric, and safety rules for the user to accept. Decides what launch-meta-ad-campaign then executes, and re-reads the strategy after a deep check to show which assumption changed. Use it after intake and before any creative is generated or any campaign is built.
日本語の概要は準備中です。原文の説明を表示しています。