Render Glassy Matte Grwm Agent Skill

render-glassy-matte-grwm

Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies

~5 makeup/skincare products step by step at a vanity, a separate ElevenLabs voiceover

narrates the routine, and every scene cut is snapped to the VO's product-name word-starts, with

~5 Playwright product overlay cards on the product-name beats, a ducked music bed, burned

captions, and a flat-lay end card. This capability is the FREE, deterministic assembly —

the Whisper-driven re-cut + hard-concat, the Playwright card render + card composite, the VO +

music mix, the caption burn, and the flat-lay end card.

This is the multi-scene beauty demo, distinct from the single-take apparel outfit-reveal

(ugc-grwm, one Seedance reference-to-video call with native lip-sync and minimal post). Here the

timeline is driven by a SEPARATE VO and the scenes are re-cut to its word-starts.

scripts/config.example.json is the worked example (DIBS Beauty "5-Step Glassy Matte Routine",

~32s 1080×1920 9:16, 12 VO-snapped cuts + 5 product cards); scripts/PIPELINE.md maps every

config block to its source step and scripts/README.md documents the free assembly.

Run

This is the FREE, deterministic assembly stage — it spends nothing. The paid inputs are

separate capabilities — the SEPARATE narration VO (create-music-elevenlabs, or a user-supplied

mp3; word-level Whisper timestamps set the timeline), ~7 Seedance scene clips one per product step

(create-video-fal), the ~5 white-bg product cutouts + the flat-lay end-card still

(create-image-gpt-image-fal), and the ducked music bed. Given the VO + .words.json + one clip

per step + the ~5 product cutouts + the music bed, render-glassy-matte-grwm re-cuts each clip to

its VO word-start window, hard-concats on the cut, renders + composites the product cards on the

product-name beats, mixes the VO over the ducked music, burns the captions, and appends the

flat-lay end card → the master. Re-cuts reuse the existing VO / clips / cutouts and cost $0.

Contract (the free assembly)

• The SEPARATE VO drives the timeline — Whisper it first. The narration is a separate track

(not a native take). Its word-level timestamps set every cut; the atempo'd VO ends shorter than

the plan expects (a 1.15× VO landed ~27.5s), so time every window to the word-starts, never to a

pre-planned grid.

• Scene cuts snap to the "step N" word-start; cards snap to the product-NAME word-start. Cut to

the next product when its step is announced; the card animates in ~1s later when the NAME is

spoken. Both happen. ~12 cuts over ~32s (cuts/10s ≈ 3.75).

• Hard-concat with a re-encode. Hard cuts on the VO word-starts, no dissolves; re-encode the

concat -c:v libx264 -crf 20 — -c copy corrupts the duration when zoompan/PNG clips are in the

chain.

• Product cards — Playwright, real cutout, PDP-verified tagline. Playwright renders the card

template at 2× scale (real white-bg cutout thumb + name + PDP tagline). The cutout must match the

REAL product, not the Seedance scene's hallucinated barrel; the tagline is verified against the

brand PDP (AI flat-lays hallucinate sublines). Composite each card onto the master snapped to its

product-NAME word-start, 1s fade-in, held until the next product is named. **PNG overlay inputs

need -loop 1 -t <dur>** — without it the PNG emits one frame at t=0 and the fade/enable filters

silently no-op (cards go invisible).

• VO leads the ducked music bed. Mix the SEPARATE VO on top of the ducked music (the VO is the

lead), loudnorm I=-14. If the host ffmpeg lacks a filter, apad/atrim to length before the mix.

• Captions — clean-white, override the preset. Clean-white captions from the VO's Whisper

words, overridden to 3 words/cue, ~3.0% font, ~20% margin, NO pill, NO shadow (the default

5-words/4.5%/18% reads too dense). Burn last. If the host ffmpeg lacks libass, render the cues as

timed PIL PNG overlays composited with ffmpeg overlay=…:enable='between(t,st,en)' at the same

placement.

• Flat-lay end card. Append the flat-lay still (ken-burns hold ~4s) — a gpt-image-2 flat-lay of

the ~5 products; do NOT trust its AI-rendered sublines for the card taglines.

• FFmpeg composite, deterministic, FREE. Re-cut, hard-concat, render + composite the cards, mix

the VO over the ducked music, burn the captions, append the end card → a 1080×1920 30fps h264+aac

master (~32s). No paid calls, no keys.