| name | vox-director |
| description | Turn ONE topic into a finished Vox-style paper-collage explainer / ad video, end to end on the Atlas Cloud API + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Use this whenever the user wants a "Vox style" video, a paper/torn-paper collage animation, a "motion collage", a narrated explainer or short ad built from AI-generated collage posters, a scrapbook-style tribute, or wants to turn a topic / product / person into a punchy narrated collage video — even if they don't say the word "Vox". Also use when reproducing Stav Zilber / rom1trs / Higgsfield-style collage ad workflows, or when the user asks for a motion collage or a scrapbook-style tribute. Triggers: "vox video", "collage video", "motion collage", "paper collage explainer", "make a collage ad", "turn this topic into a collage video".
|
Vox Director
Turn a one-line topic into a finished Vox-style paper-collage video: a bold, punchy,
narrated explainer/ad where each beat is a torn-paper collage poster that comes alive, with
voice-over, music and captions. Runs on one Atlas Cloud API key + local ffmpeg.
The look is the modern editorial paper-collage popularized by Vox explainers and creators
like Stav Zilber / rom1trs: hand-cut paper cut-outs, torn edges, tape, halftone dots,
newspaper clippings, bold flat color per beat, big cut-out headlines.
The core idea (read this first)
The Vox collage look and the collage motion are two different steps:
- The look is born in the IMAGE step. Each beat is a finished collage poster made by a
text-to-image model. All the collage DNA (torn paper, cut-outs, halftone, bold color,
headline text) lives in that image. If the image isn't a rich collage, nothing downstream
will save it.
- The motion is added after. By default an AI video model animates the whole poster (the
"living poster" path — simple, automated). For dramatic piece-by-piece assembly you cut
the poster into parts and drive them with the local keyframe engine (advanced path).
Everything hinges on the prompts. Before writing any image or video prompt, read
references/prompt-guide.md — it has the exact prompt structures that make the difference
between "a real Vox collage" and "a moving PowerPoint".
Prerequisites (check, don't skip)
echo "${ATLASCLOUD_API_KEY:+set}" — if empty, tell the user to set it (get one at
https://www.atlascloud.ai/console/api-keys) and stop.command -v ffmpeg ffprobe — required for assembly (brew install ffmpeg on macOS).python3 -c "import PIL" — Pillow, for captions/watermark overlays.
Standard workflow (topic → film)
This is the default, most-automated path. Every stage is one script, all driven by a single
beats.json per project under out/<project>/.
-
Topic → beat map. First read references/beat-layer.md (the story layer) and pick a
narrative arc that fits the topic (timeline for history, pas/bab for ads,
how_it_works for explainers, man_in_hole for transformations, …). Then write
out/<project>/beats.json following that arc: beat-1 headline must be a ≤3s hook; beat
count per duration (30s→6–8, 60s→10–12); split each beat into 2 shots (wide+detail) with
per-shot camera_move VARIED across adjacent beats (never repeat; static on the payoff)
and rich element_motion (see step 4). Each beat: narration, title_cn/title_en,
scene, bg, feel, hook. This draft is the one mandatory approval gate — show the
user the beat map before generating. Examples in examples/.
-
Pick the visual style (hybrid — do this BEFORE keyframes). Do not reuse one house style
for every topic. Read references/prompt-guide.md (§5 theme presets); pick 3–4 theme presets
(styles.THEME_PRESETS: american-retro, swiss-modern, punk-zine,
soviet-constructivist, wpa-propaganda, 70s-groovy, chinese-ink, atomic-age) that fit
the topic's era/culture/tone — or compose a custom theme by mixing the prompt-guide dimensions
(medium/era/palette/type/finish) when none fit. Match the topic, not the language (an
English film on Chinese history should look Chinese). A theme bundles the whole LOOK layer
(idiom+palette+type+finish+mood+motion). Run a bake-off and let the user pick by eye — AI
proposes, the library is the quality floor, the human decides. Set the pick as "theme":
python3 scripts/style_bakeoff.py out/<project> american-retro,swiss-modern,punk-zine,atomic-age
Set the chosen name as "collage_style" in beats.json (keyframes.py reads it).
Cadence — how long shots should be
A common mistake is one long shot per beat. On a 9:16 / social piece especially, a static
10s shot reads as dead air. Aim for a cut every ~4–6 seconds:
- Shots run 3–6s; never let a single shot exceed ~7s — beyond that the AI motion has
nowhere to go and it feels static.
- A beat's narration is ~8–10s, so give each beat 2 shots (a wide establishing shot with
the headline + a detail cut-in without it). The narration plays continuously across both;
the visual cuts mid-sentence. This is the single biggest rhythm win.
- So a ~60s film is typically ~6 beats × 2 shots × ~5s = 12 shots, not 6 × 10s.
- Reuse the wide keyframe as shot
a; generate a tighter detail scene for shot b.
keyframes.py skips any shot that already has a keyframe_url, so adding b shots and
re-running only generates the new ones.
Add a shots array to each beat (see schema). Give each shot its own short scene and
motion; set "title": true only on the wide shot so the headline shows once per beat.
beats.json schema
{
"project": "my-film", "topic": "...", "language": "en",
"aspect": "9:16",
"style": "collage",
"provider": "atlas_cloud",
"theme": "american-retro",
"arc": "timeline",
"video_model": "google/gemini-omni-flash/image-to-video",
"motion_style": "punchy",
"constraints": "strict",
theme+arc set the two big layers; element_motion per shot is the energy (make it rich — see
below). motion/collage_style/era are still read for back-compat.
Model selection (always verify IDs live)
Model IDs change — fetch the live list first: GET https://api.atlascloud.ai/api/v1/models
(no auth; keep only display_console: true). Defaults that work today:
| Job | Model | Note |
|---|
| Keyframe / collage poster | google/nano-banana-2/text-to-image | renders CN+EN text well |
| Cut out an element | youchuan/v8.1/remove-background | advanced path only |
| Animate (non-real content) | google/gemini-omni-flash/image-to-video | keeps text stable, layered motion |
| Animate (real people / brands) | kwaivgi/kling-video-o3-pro/image-to-video | Omni & Seedance BLOCK celebrities |
| Narration | xai/tts-v1 | clean, multilingual, voice_id |
| Music | minimax/music-2.6 | is_instrumental: true |
See references/models-and-gotchas.md for the full model-choice reasoning and every
API / ffmpeg gotcha (auth header, curl downloads, no-libass captions, content blocks, etc.).
Read it before debugging any failure — most failures are already documented there.
Backends are pluggable. Every API call goes through a provider (scripts/provider.py);
Atlas Cloud is the default and only backend today. Set "provider" in beats.json to route to a
different backend once one is added — the stage scripts don't change. scripts/provider.py's
run_jobs() also does the submit/poll with auto-resubmit on a stalled or failed job.
Advanced: element-level motion collage
The standard path animates the whole poster (great, automated, "living poster"). For the
dramatic pieces-fly-in-and-assemble motion collage (à la cr7v2), or to animate real
people with full control and zero content filters, cut each poster into independent
elements and drive them with the local keyframe engine (no video model needed).
Read references/local-engine.md. In short: extract_elements.py (crop + background-removal
- residue/erase cleanup) →
motion.py (Layer + keyframes, fly_in/slap/drop/pop_settle
easings, procedural confetti/starburst, camera zoom+shake+whip, frame render). Pieces fly
back to their original positions on a blurred-placeholder backdrop, so the assembled
frame reconstructs the original poster.
Editions
- Auto edition (this skill): topic in, film out, all on Atlas.
- Manual prompt-pack: if the user isn't on Atlas, just produce the beat map + the per-beat
image prompts + the per-clip motion prompts + the narration script for them to paste into
any generator. The creative engine (the prompts) is identical.
