Assemble a viral iOS "AirDrop" notification-carousel video ad (≈6–8s, 9:16) from a brand line plus 6–16 real product photos — a native AirDrop share-sheet card ("Brand would like to share a ___ · Decline / Accept") springs up and its preview window CYCLES through the products, landing on a range/lineup payoff with an Accept tap; a chime + soft per-swap ticks track the swaps. DETERMINISTIC assembly — an HTML card (real DOM text) rendered to PNG via headless Chrome, chroma-keyed, its magenta window refilled per-product in PIL, then animated + audio-synthed with FFmpeg. FREE (no paid model calls); the recipe supplies the brand line, product images, and payoff and gates the only optional paid step (a hero shot when the brand has NO usable photo → create-image-fal). Use for the airdrop-notification-carousel 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。
The free, deterministic renderer for the airdrop-notification-carousel video ad format — the viral iOS "AirDrop" trend where a native share-sheet card ("Brand would like to share a candle · Decline / Accept") springs up on the phone and its preview window flips through a carousel of real product photos, landing on a range/lineup payoff with an Accept tap.
This is a DETERMINISTIC composite — no generative video, no AI-rendered product.
A real-DOM AirDrop card is rendered once to PNG (headless Chrome), chroma-keyed, and
its preview window is refilled per-product in PIL, then animated + audio-synthed with
FFmpeg. The whole point of the format is crisp system-UI text and real product
photography, both of which a video model would smear. This capability makes no paid
calls; the recipe gates the only optional paid step — generating a hero product shot
when the brand has NO usable photo at all (→ create-image-fal).
Default output ≈ 6–8s, 1080×1920, h264 + aac. Duration is DERIVED, not trimmed —
first_hold + (N-1)·per + final_hold. Add images or raise per to lengthen.
scripts/build_card.py — brand params → chrome.html + chrome-pressed.html: the
AirDrop card on a green page (#00e000) with a magenta preview window
(#ff00ff) and a solid brand band (wordmark SVG or text + tagline). Real DOM text —
AirDrop, Decline, Accept, and the brand line are DOM/SVG, never AI-rendered.scripts/one_shot.py — glue: build_card → headless-Chrome (Playwright) fullPage
screenshot of both card states → compose_carousel. One --config, one MP4.scripts/compose_carousel.py — the render engine: green-key the card → detect the
magenta window → fill it per-product (cover-crop) → blurred per-product backdrop +
push-in → card spring-up (iOS ease-out-back) + carousel + Accept tap → synth audio
(whoosh on entry, chime on land, a tick per swap, a pop on the tap) → encode h264+aac.scripts/config.example.json — the shape of the brand config the recipe binds
(brand-neutral worked defaults; replace every /abs/path/... placeholder).message, the product images + order, the final_image payoff, and timing.per
(pace).brand, wordmark_svg, tagline (a real stated proof
point only), accent and band_color. If not passed, the scripts fall back to a
neutral iOS blue #0A84FF / light grey #F2F2F7 — pass the brand's own colors.#00e000 green = page background, keyed to the card's alpha. #ff00ff magenta
= preview window, replaced per product. Neither color may appear in the card art or
any product photo — a product image containing near-pure green or magenta gets
keyed/misread. Swap the image or tighten the window_mask thresholds if it bleeds.
final_image) should
read as "the whole line" (lineup / family / all-shades).1M+ sold tagline must be the brand's OWN stated figure,
not filled from a brand-kit proof section.per; never cut the audio.numpy + Pillow, and ffmpeg/ffprobe on PATH.pip install playwright && playwright install chromium). If Playwright is unavailable, run build_card.py, screenshot
chrome.html / chrome-pressed.html (fullPage) → chrome-green.png /
chrome-green-pressed.png via the chrome-devtools MCP, then call compose_carousel.py
directly.watch (QC the final master). The recipe gates create-image-fal (optional hero shot
when the brand has NO usable product photo) — the only paid, proxy-routed step.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。