Generate an AI creator talking to camera, saying an approved script, as one continuous track — H3 Max reference-to-video through the GooseWorks fal-proxy (bills the Ads agent). Plans takes on line boundaries under H3's 15s cap, dry-runs a cost estimate, generates the first take alone so its voice can be locked and passed to every later take, joins takes with measured 0.10s dissolves, and moves each line's timing onto the words actually spoken. Use for any format with a generated creator speaking a script (split-screen, screen inserts, talking-head ads).
npx gooseworks install --all # then, in Claude Code, Cursor, or Codex: /gooseworks use the create-creator-takes-h3 skill
A generated creator who says an exact script, with one consistent face, room and voice across several takes.
| Script | What | Cost |
|---|---|---|
make_character.py | build the creator still from the user's choices, one shot | paid (one still, cents) |
plan_takes.py | split lines into takes (under 15s each) and write the prompts | free |
run_takes.py | generate the takes, dry run unless --go | paid (H3 Max, ~$0.16/s at 1080P) |
join_takes.py | join into one creator track | free |
align_beats.py | move line timings onto the spoken words | free |
character-prompt.json is the realism prompt for the character still. Do not fill it by
hand. make_character.py fills every slot and calls create-image-fal, because a
hand-filled prompt left slots blank and produced the composite face the formula warns about,
and different runs filled it differently.
# the user's person, one command, one still. --dry-run prints the prompt and spends nothing.
python make_character.py --age 34 --gender woman --ethnicity "South Asian" --hair "shoulder-length black hair, slightly frizzy at the crown, one side tucked back" --wardrobe "plain charcoal crew-neck t-shirt, slightly creased" --scene "a lived-in home office, a bookshelf softly out of focus behind her" --out work/character # writes character.png AND character.json
python plan_takes.py --beats cutlist.json --character character.json --out work/takes
python run_takes.py --spec work/takes/takes.json # dry run: plan + estimate
python run_takes.py --spec work/takes/takes.json --only t1 --go # after the user approves
python run_takes.py --spec work/takes/takes.json --go # the rest, voice chained
python join_takes.py --spec work/takes/takes.json --end <reel length> --out work/creator.mp4
# caption-burn: transcribe.py --media work/creator.mp4 --out work/creator.words.json
python align_beats.py --beats cutlist.json --words work/creator.words.json \
--out cutlist.aligned.json --max-end <creator.mp4 length>character.json, which make_character.py writes for you:
{"image": "character.png",
"identity": "<age + gender + look from the user's brief>, <hair>, <wardrobe>",
"environment": "<the real room in the approved still>, window daylight",
"delivery": "<the tone the user chose>. Whatever the tone, keep the face relaxed: an over-energetic read can give a constant grin and busy hands that read as AI."}The user chooses who the creator is. Ask for age, gender and ethnicity, plus hair,
wardrobe and room, then pass them to make_character.py. Those six are required arguments, so
there is nothing to forget and nothing to invent. There is no default person: never
copy a look from an example, a reference build or a demo reel.
This is now enforced, not advisory. plan_takes.py rejects an identity that is still a
placeholder, or that states no age, or that states no gender. It was advisory once and the
docstring carried "a man in his late 20s ..." as an example: that got copied verbatim, the
old non-empty check passed it, and every build produced the same unrequested man. An
unspecified person is exactly the ambiguous composite face the realism formula warns about,
and it is what a reviewer sees as "obviously AI".
delivery now defaults to calm and conversational. The default used to be energetic,
which this file already warned "can give a constant grin and busy hands that read as AI", so
avoiding a known failure depended on remembering to opt out. Pass delivery to override.
identity and environment go into every take word for word. Write them once from the
approved still, then never retype them: a person described two ways drifts between takes.
These are the user's calls (the recipe's choices), never defaults of this atom:
identity) — age, gender, look. Asked of the user; no default person.environment) — the room behind them, written from the approved still. Asked of the user.delivery) — how they speak. Asked of the user; if missing, plan_takes.py
falls back to a neutral conversational read and prints a note.reference_audio_urls). A robotic or mismatched voice in t1 is in every
take. If the user rejects it, --reseed t1 and generate t1 again.delivery, not by editing
the prompt file.plan_takes.py refuses them.prompt_expansion_mode: disabled.--split-at 6.3,14.5 joins the takes exactly at those line boundaries: the
screen-insert format joins where an insert ENDS, so the cut is hidden under the screen.
The voice runs under inserts too, so every line (creator or product beat) is in a take.xfade with a late offset silently concatenates instead of overlapping.--mannerism passes a muted
motion-reference clip. Its gaze transfers, so check the eyeline on every frame. Never
use another brand's creator footage.character-prompt.json sat in this directory read by no
script, with the instruction "fill its slots, generate 2-4 options, let the user pick one".
Slots got left blank, every run filled them differently, and the documented workflow was
iterative by design. Use make_character.py; it refuses a blank slot and an out-of-range age.plan_takes.py shipped
with a literal backspace byte where \b was meant, so every identity failed and the skill
could not run at all. A guard is not tested by reading it: run it against one input it must
ACCEPT and one it must REJECT. grep -c $'\x08' <file> catches this class.--hair, --wardrobe, --scene, or a
different --seed, which reshuffles which three skin imperfections are asked for) rather than re-rolling the same brief; an unchanged payload
with a pinned seed reproduces the same image and wastes the spend.identity) — age, gender, look. Asked of the user; no default person.environment) — the room behind them, written from the approved still. Asked of the user.delivery) — how they speak. Asked of the user; if missing, plan_takes.pyFull video production sequence with script review, actual ingredient choices, controlled generation, editing, evidence-based quality review, polish, captions and delivery. A host binding supplies project storage, authentic approvals, provider access and billing.
Build a vox-pop street interview video ad. An interviewer with a handheld mic asks passers-by one question about the brand's product, they give blunt wrong guesses, one gives the real answer, and the cut lands on a branded end card. Generates the takes through the GooseWorks fal proxy (Seedance 2.0 with native voice), then grades, re-cuts, captions and gates them locally. Use for the street-interview format.
Write the words of a short-form video ad (voiceover, dialogue, chat bubbles, on-screen lines) the way performance creative teams do instead of from a blank page. Builds the script from the buyers' own words, the beat sheet of an ad that already works and three deliberately different angles, filters them with a rule check and a second non-Claude model, and takes the strongest into the review with the other two as one-line swaps. Use it in every video ad run before any paid step, and whenever the user asks to write, rewrite or improve a video ad script or says a script sounds generic or AI-written.