Assemble a 3D-CGI app sizzle — nano-banana CGI plates (blank-glow floating phone + a CGI studio with rim-light + placeholder burst shapes; studio look and phone finish come from the recipe choices) plus PIL compositing of the REAL App Store screenshots onto the bezel + burst-out overlays, driven by Kling 3.0 i2v steady-float per beat with a per-beat Ken-Burns FFmpeg push-in fallback when Kling garbles the UI, then VO/music mix (sidechain duck, loudnorm) + 1.15x speed + anti-AI grain finalize. The on-screen UI, any faces in it, and the wordmark are ALWAYS real assets composited via PIL — never AI-rendered. The paid steps (plates, i2v clips, VO, music) are separate capabilities; this ships the config + PIPELINE + FREE assembly and the recipe orchestrates the spend. Use for the cgi-app-sizzle video 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。
Assembles the 3D-CGI app sizzle video format: a phone floats in a CGI studio while five or six app features demo one per beat — each beat bursts REAL App Store UI elements out of the phone in 3D with rim-light + bokeh, then everything collapses back into the screen at a value-prop climax + a brand end card over a music bed. It reads as an Apple-keynote product film, not UGC and not a physical-product shoot.
The worked example (scripts/config.example.json) is MasterClass: a gold phone in a
smoky-black studio with an amaranth rim-light, an "Eryn" keynote-cadence VO, a premium-tech
piano/synth bed, and a "200+ classes. One app." climax. Those are one example, not defaults.
Creative calls the user makes (the recipe's choices, asked in one round before any paid
step). The demo's value is only an example.
studio_look — background, rim-light colour, bokeh; also the end-card canvas + bar.
Asked of the user; the demo used smoky-black #0A0A0A + amaranth #E32652 rim-light.phone — the phone model/finish in every plate. Asked; the demo used a gold/champagne
titanium iPhone 15 Pro.narrator_voice — the VO voice. Asked; the demo used ElevenLabs "Eryn".vo_delivery — how the VO is written and read. Asked; the demo used a restrained
Apple-keynote spec-sheet cadence.music — the bed's genre/mood. Asked; the demo used a premium-tech underscore.This capability ships the recipe (scripts/config.example.json) + a config→step map
(scripts/PIPELINE.md) + the FREE-assembly how-to (scripts/README.md). It documents the
FREE, deterministic assembly between the paid model calls:
--anchored on beat 1 so the phone/studio stay
identical across beats.scene-NN-composite.png;
bake real burst-out overlays (e.g. climax portrait tiles, rim-light baked before
rotation) around the plate. The on-screen UI + faces + wordmark are ALWAYS real assets —
never AI-rendered, so no claim is invented and nothing reads fake.zoompan, heavier on the climax) — the shipped demo used this
path for the feature beats.See scripts/README.md for the full FREE-assembly detail and scripts/PIPELINE.md for the
config-field → source-step map.
Config-and-PIPELINE capability (no re-built runnable pipeline here). Copy the
structure of scripts/config.example.json → config.json, fill the creative fields from the
recipe choices (never the demo's values), rebuild the brand/beats/screens, and follow
scripts/PIPELINE.md:
VO first (locks the timeline) → nano-banana CGI plates → PIL screen composites → burst-climax overlays → Kling i2v clips (Ken-Burns fallback per garbled beat) → PIL end card → captions → sidechain-ducked mix → 1.15x speed + grain.
Output: 1080x1920, ~22s H.264 (+ AAC music). 5-6 feature beats + PIL end card.
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。