Scenario UGC Creator Video

Overview

UGC is a register, not a length: content that reads as a person talking into their own phone, not a brand talking through a camera crew. Everything in this skill serves that register, and most failures come from importing ad craft into it. This skill routes the production; mechanics live in the sibling skills named per lane. Connection and the core loop: see the

scenario

skill in this repo. If a sibling skill named here is missing from your available skills, ask the user to install it (

npx skills add scenario-labs/skills --skill <name>

); unattended, proceed from tool schemas and flag the gap.

Two rules are non-negotiable. The product is never generated: demo shots start from an uploaded photo or footage of the real product (

scenario-product-shots

for stills). And the words are never invented: no fabricated testimonials, review counts, metrics, medical or financial claims, or legal copy; speak only lines the user supplied or approved, and prefer observable statements ("the texture looks lighter") over claims ("this cures acne").

Quick reference: route by speaker lane

Discover members with

recommend

, passing the lane's capability and the user's own words: it ranks by measured cost and latency and names the purpose-built pick, where a capability-worded

search

returns hundreds of keyword hits with nothing to choose between them. Read

next_step

before taking a pick, per the

scenario

skill. Keep

search

for a member you can already name. Never assert a generative model's id as a constant. Scenario's own single-purpose tool models are named outright below: there is exactly one of each, so discovering them would only re-derive a constant.

Lane	Route	Contract
Portrait plus speech audio	Talking-avatar members ( `img2video` )	`scenario-kling`
Existing footage, new words	Lipsync members ( `video2video` ), audio or `text` , never both	`scenario-kling`
Recorded delivery, different face	Motion-control members ( `video2video` , say "motion control" in the `recommend` prompt or lipsync members come back): character still plus the recording as driving `video` , `keepOriginalSound` keeps the voice; output lands at the member's own size, the still lending only its orientation	`scenario-kling`
Generated creator speaking natively	Native-audio video families ( `txt2video` ), dialogue in quotes with the delivery named (pace, tone, one gesture)	`scenario-veo` , `scenario-seedance` , `scenario-kling`
Faceless voiceover	B-roll clips ( `txt2video` ) plus TTS narration ( `txt2audio` )	`scenario-video` , `scenario-elevenlabs`
Product demo inserts	Image-to-video off the uploaded product still	`scenario-product-shots` , `scenario-video`
Captions, cut, 9:16 master	Assembly tool models; text cards as image layers	`scenario-video-assembly` , `scenario-text-overlay`

Script in six spoken beats: hook (one concrete tension or result), context (why this speaker cares), product moment, proof (visible demo or a user-supplied fact), turn (objection answered or before-after), close (soft CTA). Write for the mouth, not the page: contractions, false starts allowed, no taglines. Spoken pace runs near 2.5 words a second, so a 25-second ad is roughly 60 words, but that is a first guess and avatar members undershoot it: observed rates run 1.76 to 1.94 words a second, and one member padded a 60-word script with 21s of silence instead. Time the returned clip before assembling, then trim the silences where there are any and cut the script where the delivery is simply slow. The compositor has no cut inside a layer, so a trim is one layer per kept segment, each with its own

trimStart

and

duration

Keep the register in every visual prompt: phone-height framing, available light, a real location with clutter, natural skin texture, one handheld drift at most. Cinematic grammar (dolly moves, golden-hour rim light, shallow anamorphic looks, graded color, retouched skin) reads as an ad and kills belief. Compose 9:16 natively, reframing any non-vertical still a lane consumes (the avatar portrait, a motion-control character still, the product photo) per

scenario-formats

before generating; a cropped 16:9 master frames like television.

Worked example: 25-second founder ad from a portrait

Brief once: offer, platform, runtime, the facts the founder may claim, tone. Collect the portrait and the real product photo, then run without stopping.
Create this run's collection before the first generation (
```
collection_create
```
, catalog write lane,
```
name
```
only), then
```
collection_add_assets
```
each keeper as it lands; its returned
```
itemCount
```
is the receipt.
Draft the six beats at about 60 words and confirm the wording with the user; the script is a claims surface, not just copy. Unattended, keep every line to wording the brief already supplied and cut any beat that would need a new claim.
Voice:
```
upload_asset
```
the founder's recorded narration, or generate TTS per
```
scenario-elevenlabs
```
when they want a stand-in voice they approved.
```
recommend
```
with
```
capability="img2video"
```
and the brief in the user's words; pick from its ranked list by input contract (a script-taking member when the speech exists only as text, an audio-taking one when a recording exists), then by whether the member can be told not to burn in captions: some hallucinate gibberish subtitles that no negative prompt suppresses, and the ones with a switch cost several times more, which
```
recommend
```
prices for you.
```
upload_asset
```
the portrait. Prompt the speaker's hands empty and the set free of products: avatar members invent props and label type.
```
model_run
```
with
```
dry_run=true
```
first: avatar members sit far apart on price, so quote before spending.
Run for real with
```
wait=false
```
, then
```
jobs_wait
```
with the returned job id, re-called with
```
pending_job_ids
```
on timeout, never a second
```
model_run
```
.
Demo insert: animate the uploaded product photo with an image-to-video member (
```
scenario-video
```
), 3 to 5 seconds, one micro-move. Whether
```
aspectRatio
```
survives a start image is per member and the schema note can be wrong either way, so read
```
width
```
and
```
height
```
off the returned asset rather than assuming the ratio held.
Assemble with
```
model_scenario-compose-video
```
per
```
scenario-video-assembly
```
: talking head as the spine, insert cut over beats three and four, product-name card from
```
scenario-text-overlay
```
as an image layer, dropped outright when no approved product name exists, since inventing one is the fabrication the brief forbids. Every overlay layer needs an explicit
```
width
```
and
```
height
```
or the compositor scales it, and
```
durationMode: "custom"
```
pins the master's length against image layers that would stretch it. A succeeded compose job is not proof the layers drew or landed where sent: pull a frame from the composite and confirm the card is present and placed before delivering. Captions come last, on the finished cut, from the captioner
```
scenario-video-assembly
```
discovers with
```
recommend
```
(two exist, so no fixed id), positioned inside the platform's safe zone: the compositor has no text layer.
```
asset_display
```
the master. Gate every generated clip, the talking head included: take the frames from the platform, the free
```
firstFrame
```
and
```
lastFrame
```
off
```
asset_get
```
first and
```
model_scenario-video-to-image-seq
```
when a mid-clip frame is what settles it, then verify them against the uploads (
```
scenario-asset-analysis
```
); a local extraction is not a substitute at any budget, because it yields no asset to file or audit and the gate stops being traceable; an invented product in the speaker's hands or legible generated type fails a clip exactly like label drift on the insert. Report spend by summing this run's own job records by job id:
```
jobs_list
```
is project-scoped and over-reports, and
```
usage
```
's headline figure is project-lifetime.

Common mistakes

Writing ad copy and handing it to a mouth: alliterative taglines collapse on a talking head; read the script aloud before generating.
Fabricating social proof: an invented "10,000 five-star reviews" is a claim the user never made; keep numbers and testimonials to supplied wording.
Prompting the creator like a commercial: tripod framing, perfect light, and a spotless studio kitchen read as an ad; imperfection is the format.
Passing both audio and
```
text
```
to a lipsync member: exclusive inputs; pick one.
Skipping
```
dry_run
```
on avatar and lipsync runs: per-member pricing varies too widely to guess.
Generating the product or any on-screen text: the product comes from the uploaded photo, type is overlaid in assembly. Native-speech members can caption the quoted line, and those captions collide with the ones the captioner places in the safe zone, so end every dialogue prompt with "no subtitles, no on-screen text". There the line is the only lever and costs nothing, and it is not a guarantee (one native-speech member captioned anyway at authoring time), so pull a frame before compositing; avatar members can hallucinate subtitles no prompt suppresses, which is why step 5 prices their caption switch.
One 40-second b-roll or generated-creator take: generate per-beat clips and cut on the beat turns; single long takes drift and cost more to retry. A talking-head script stays one take, trimmed in assembly.
Cropping a landscape master to 9:16: heads and captions land outside the safe zone; compose vertical from the start.

scenario-ugc

NPX Install

Tags

SKILL.md Content

Scenario UGC Creator Video

Overview

Quick reference: route by speaker lane

Worked example: 25-second founder ad from a portrait

Common mistakes