explainer

Requires OFOX_API_KEY — create one at https://app.ofox.ai. Turn an article, doc or release note into a short explainer clip — one person to camera, or a voiceover over illustrative footage. The user supplies the source text and the model generates the speech; audio cannot be uploaded, measured. A 30-second clip holds about eighty spoken words in eight sentences — measured, and well under a tenth of a 1,200-word post — so this skill does not summarise an article, it picks the single idea worth saying and helps choose which one. Use when a user asks to turn writing into a short spoken video, e.g. "make a 30-second explainer from this blog post", "explain this feature in a short video", "turn our changelog into a clip", "a quick video explaining what this paper found". Do not use for a scene between people (see seedance-short-drama), a brand or product ad (see seedance-ad-creative), a handheld creator clip (see ugc-ads), or when the user already has both a portrait and the finished words (see talking-head). Budget sentences as well as words — each sentence boundary costs about 0.7 seconds of silence, so a script with more sentences runs longer at the same word count.

explainer: one idea from the writing, said once

Takes something written — an article, a README, a release note, a paper — and produces a short clip of it being said out loud. The user supplies the source; this skill picks the one idea that fits, writes it as spoken words, and sends it to be generated.

This skill is a thin, scenario-specific layer over ofox-video-core. It owns the idea selection, the explainer prompt craft, the brief, the defaults and the pre-generation cost estimate; ofox-video-core owns talking to the Ofox API correctly and safely (the OFOX_API_KEY handling, the no-resubmit rule, error-code mapping, download/verification, and reporting the downloaded file's absolute VIDEO_PATH). Read that skill's safety contract before using this one — it is not restated here.

Shared prose is linked rather than copied: the prompt formula, camera and delivery vocabulary, the word-rate tiers and the negative-list items are in ../ofox-video-core/references/prompt-structure.md; the pre-prompt question rules in ../ofox-video-core/references/creative-brief.md; the spend rule in ../ofox-video-core/references/approval-gate.md.

The request this skill almost always receives is not the one it can fill

People ask for "a 30-second video of this article". The arithmetic says no, and it says no by a wide enough margin that the honest move is to say it in the first reply rather than after the bill.

Sentences cost seconds too — the budget is not words per second alone

🚨 This section used to be headed "a thirty-second clip holds about ninety spoken words". A 30-second run disproved it. The old number came from multiplying a 20-second clip's rate by 30, and the thing that multiplication misses is that every sentence boundary costs about 0.7 seconds of silence. A script with more sentences takes longer at the same word count.

The two word-rate tiers and the gallery cases behind them live in the shared file — prompt-structure.md → "Dialogue and sound" → "Density — two tiers, not one" — and are not restated here; what this skill has measured on this API is below. The tier that applies to an explainer is monologue / talking head — one person speaking continuously. The other tier, dialogue drama at 0.4–1.7 words/s, measures a different shape: two people, with silence between their lines. It is a floor here rather than a budget.

The budget formula, from the 30-second run:

text

speech span (seconds) ≈ words / 3.56 + 0.7 x (sentences − 1)

3.56 words a second is the measured rate while actually speaking; the second term is the pauses between sentences. Checked against its own run: 80 words in 8 sentences predicts 27.4s, and the delivered speech span was 28.13s. Then leave room at both ends — that clip started speaking at 0.567s and finished 1.39s before the last frame.

Clip	A safe script	Which is	Share of a 1,200-word article
10s	~25 words, 2–3 sentences	one thought	2%
15s	~40 words, 3–4 sentences	a short paragraph	3.3%
20s	~55 words, 5 sentences	a paragraph	4.6%
30s	~80 words, 8 sentences — measured, fits with 1.39s to spare	a claim, its reason, and what to do about it	6.7%

Only the 30-second row is measured. The others apply the same formula with the same headroom and have not been run.

Ninety words in thirty seconds does not fit. By the formula, 90 words across 8 sentences needs 90/3.56 + 4.9 = 30.2s of speech span — longer than the clip, before any opening or closing beat. The failure mode is the expensive one: overrunning comes back rushed, garbled or cut off, which costs the whole clip, while under-filling costs a pause at the end. Round down.

Count the sentences, not just the words. Two 80-word scripts can differ by several seconds — short punchy sentences are slower on this model than the same words in fewer, longer ones. That is the opposite of how most people estimate, and it is the practical half of this section: a script that fails the budget can often be fixed by joining sentences rather than cutting words.

What kind of evidence this is. Both tiers started as counts of gallery prompt text against clip length: real prompts and published clips, but unrecorded platforms and parameters, and no measurement of what this API delivers. That is still what the 3.5 / 5 ceiling is, and the CJK figures are still exactly that and nothing more. The English budget is now this model's own, measured twice:

Run	Script	Speech span	Overall rate	Rate while speaking
edef379e (20s)	59 words	19.33s	3.05 w/s	not separated
42d8b5c3 (30s)	80 words, 8 sentences	28.13s	2.84 w/s	3.56 w/s

The two overall rates differ, and the second run explains why. Splitting speech from silence showed 22.49 seconds of actual speaking and 5.64 seconds of internal silence — 7 pauses, matching the script's 7 sentence boundaries exactly, about 0.7s each. So the overall rate is not a property of the model; it falls out of how many sentences the script has. A denser-sentence script scores a lower "words per second" while speaking at the same speed.

That is why the budget above is a formula rather than a rate, and why the old 90-word row could not survive: it multiplied a 20-second observation by 1.5 and carried no term for the pauses.

Until that run this was an extrapolation across tiers, and that is a mistake this repo has already made once. Every word rate measured here before today came from two-person dialogue, and handing the dialogue band to a continuous speaker is a category error rather than a conservative estimate — the dialogue tier's low floor is not somebody talking slowly, it is words spread across a clip where most seconds have nobody speaking at all. talking-head shipped that error and had to correct it. The monologue tier now has measurements of its own instead.

A third observation, on another model, and that is still not a law. talking-head's first paid run measured 3.16 words a second overall on alibaba/wan-3.0-prime (2026-09-16). It is close to this skill's two, which is the reassuring direction — but its speech and silence were never separated, so it cannot be compared against the 3.56 figure, and the sentence-boundary term has been measured on one run only. Nothing has been measured in another language or at another resolution. Two data points on one model, agreeing about why they differ, is exactly as much as this file claims.

⚠️ Thirty seconds is now measured; the rest of the table is not. The 30-second row comes from a real 30-second clip. The 10, 15 and 20-second rows apply the same formula with the same headroom and have not been run at those lengths — the closest evidence is the 20-second clip, whose script was written against the older, looser budget and still fitted.

So the product is one idea, said once

Eighty words is not a summary of a 1,200-word article — it is well under a tenth of it. It is a claim, its consequence, and one concrete detail. That is not a degraded explainer — it is what a short explainer has always been — but it has to be said out loud before a user pays for something they thought was a summary:

A 30-second clip holds about eighty spoken words — roughly one paragraph and under a tenth of your article, and that is measured rather than estimated. It will not summarise the piece. What it can do well is land one idea from it — so the useful question is which idea, and the next section is how to pick.

Never quietly compress the article into eighty words instead. A summary squeezed to that length becomes a string of abstractions that means nothing to someone who has not read the source — the worst of both products. One concrete idea, fully said, beats five ideas gestured at.

If the user genuinely needs the whole article covered, the honest answers are: a series of clips (priced below, and it has a real continuity problem), a narrated slide deck, or written text. Say which you think fits before quoting.

Picking the idea

This is the work. Everything after it is mechanics.

The procedure

1. Read the source and list its candidate ideas — usually three to five. A candidate is a claim, not a section heading: "the migration is automatic" is a candidate; "Migration" is not.

2. Write each one as the sentence that would actually be spoken. Not a label, the words. This is the step that kills most candidates: an idea that cannot be said in one or two plain sentences will not survive the clip either.

3. Score each against four tests, all four of which have to pass:

   Test	Fails when
   Stands alone — does it make sense to someone who has not read the article?	It depends on a definition, a number, or a previous paragraph
   Concrete — is there a specific thing, number or action in it?	It is a category ("improved performance", "better developer experience")
   Fits the budget — does the spoken form come in under the clip's word count?	It needs a subordinate clause to be true
   Worth 30 seconds of someone's attention — is it the thing the reader should remember or do?	It is true and nobody's decision changes because of it

4. Offer the two or three survivors to the user, as the actual sentences, and let them choose. This is a must-ask axis — it is their article, and no model can tell which idea they meant. If they say "you pick", pick the most concrete one, name it in the recap, and let the approval gate be the check.

Where the good candidate usually is

Not in the introduction. In practice the sentence worth saying is:

• the one number in the piece that changes a decision;
• the thing that is now true that was not true before — a release note's actual change, a paper's actual finding;
• the counter-intuitive line, the one a reader would not have guessed;
• the action the article is asking for.

A title is usually a bad candidate: it was written to be clicked, so it is vague on purpose, and vague is what one paragraph of speech cannot afford.

Worked selection — a 1,100-word release post

Source: a post announcing a database client release. Candidates, each written as it would be spoken, with the verdict:

Candidate	Spoken form	Verdict
The release is out	"Version 4 of the client is out today, with a lot of improvements."	Fails concrete and worth-it. Nobody's decision changes
Connection pooling was rewritten	"We rewrote connection pooling on top of a new scheduler with backpressure."	Fails stands-alone. Means nothing without the article
Reconnects no longer drop queries	"Version 4 stops dropping queries when the connection blips. If you wrapped every query in a retry, you can delete that now." — 22 words	Passes all four. Concrete, a reader acts on it
Old versions stop getting fixes in March	"Version 2 stops getting security fixes in March, so upgrading is now a date rather than a preference." — 18 words	Passes all four. A number, a decision

Two survivors go to the user. The recap names which one they picked and says the clip carries that one and not the post.

Before anyone pays: what is measured here, and what is not

This skill has two paid runs of its own, and the second one overturned the number the whole file used to be built on. Both bytedance/seedance-2.5 on byteplus, 480p, text-to-video with nothing attached, --generate-audio left at the server default so the speech came back on the track, and both read afterwards — audio measured and transcribed, frames extracted — rather than called done at STATUS completed.

Run	Shape	Cost
edef379e-9ac0-41c9-ab59-6378d030239e (2026-09-16), seed 623333235	20s, presenter-to-camera, 59 words	$2.20
42d8b5c3-31f4-41d2-90eb-b07a3181b465 (2026-09-17), seed 1021654967	30s, 16:9, the Voiceover template, 80 words in 8 sentences	$3.30

The first run — 2026-09-16

Question	Measured	How
Speech rate	3.05 words a second overall	59 words across a 19.33s speech span. silencedetect at -30dB puts the first word at 0.399s and the last at 19.729s, with 7 internal pauses
Truncation	None	A whisper tiny.en transcription returns all 59 words, in order, with nothing added or dropped
The closing beat	It fitted	0.335s of silence between the last word and the last frame. The template asks for that beat and the clip had room for it — under-filling by a hair is what bought it
Whether a 30-second clip behaves the same	❌ It does not	This row used to say "not measured" and carried the 90-word extrapolation. See the second run

⚠️ One measurement here was nearly reported backwards, which is worth knowing before repeating it. A first pass with silencedetect at a 0.35s minimum found no trailing silence, and the tempting reading was "a script at 3 words a second squeezes the closing beat out". Wrong: the beat is plainly there in the frames — mouth closed, expression held — and the pause is 0.335s, sitting just under the threshold that was looking for it. A tool not reporting something is not the thing not happening. Check that the threshold can see the size of the thing you are asking about before concluding from its silence.

What that run does not establish: one run, one script, English, 480p, 20 seconds, presenter-to-camera. A faster or slower script, another language and another resolution are all still unmeasured here.

The second run — 2026-09-17, and it cost this file its headline number

Job 42d8b5c3, 30 seconds, the Voiceover template (no visible speaker), 80 words in 8 sentences, $3.30. It closed this skill's two largest gaps at once: the duration it is named for, and the shape it had never generated.

Question	Measured	How
🚨 Does "about ninety words" hold at 30 seconds?	❌ No	Speech span 0.567s → 28.695s = 28.13s for 80 words. Split into speech and silence: 22.49s speaking, 5.64s of internal silence in 7 pauses — exactly the script's 7 sentence boundaries, about 0.7s each. Speaking rate 3.56 w/s; overall 2.84 w/s. By that model 90 words in 8 sentences needs 30.2s of span, which does not fit in a 30s clip
The budget formula	span ≈ words/3.56 + 0.7 x (sentences − 1)	Predicts 27.4s for this script; delivered 28.13s
Truncation	None	1.39s of tail left over. The script fitted with room
The voiceover shape itself	✅ It works	No person anywhere in 30 seconds; a slow continuous push with no cut; no on-screen text at all; and the ending holds — the frames at 22s and 29.5s are nearly identical, on a recessed button, exactly as the template asks
Whether the 20s and 30s rates conflict	They don't	3.05 and 2.84 are the overall rates of scripts with different sentence densities. The underlying speaking rate is the thing that is stable, and only the 30s run separated it

What this run does not establish: one run, one script, English, 480p, 30 seconds, voiceover. The 0.7s sentence-boundary cost is measured once, on one script's 7 boundaries — it is the most load-bearing number in this file and the least replicated. A faster or slower script, another language, another resolution, and any duration past 30 seconds remain unmeasured.

The rest of what this file rests on:

Claim	Strength
The English budget formula — 3.56 words a second while speaking, plus ~0.7s per sentence boundary	Measured on this model, once, at 30 seconds (42d8b5c3). The 20-second run agrees on the overall figure it can supply (3.05 w/s across a script with 7 pauses of its own) but never separated speech from silence, so it corroborates rather than replicates. talking-head's 3.16 w/s on alibaba/wan-3.0-prime is a third overall rate on a different model, also unseparated
A supplied audio track does not become the clip's audio	Measured, job d8561509-dcc6-4f2c-8864-a193cd239b14, 55 cents, 2026-09-15 — the input was near-continuous speech, the delivered track was sparse, correlation 0.41. The model generates its own voice
The model renders a photoreal person speaking, from text alone	Measured, six bytedance/seedance-2.5 text-to-video jobs of 20–30 seconds built entirely around photoreal people, all completed, five of them carrying spoken lines. On five of the six only the picture and the timing were checked; the sixth is this file's own run above, where the audio was transcribed against the script
A photoreal person in an attached image is refused at submission on bytedance/seedance-2.5	Measured 2026-08-30, input_moderation_failed, nothing billed. It decides the continuity limits below
Asking this model for music can fail output moderation on copyright	Measured once, unbilled
Text rendered from a description comes back invented or garbled; text approved on a still and attached as a frame is preserved	Measured, several jobs. It decides the on-screen-text section below
The ceiling the budget sits under — the monologue tier at 3.5 words/s English and 5 characters/s Chinese — and the CJK budget of 4 characters/s	Gallery practice — prompt text counted against clip length across a public corpus, not Ofox runs. It is a Seedance 2.5 collection and this skill's default is Seedance 2.5, so the model at least matches; but for the community entries the platform that produced the clip is unrecorded. Nothing here has been run in Chinese or Japanese, so the character-per-second rows are exactly as strong as they were
A voiceover with no visible speaker	Measured, job 42d8b5c3 (2026-09-17, 30s, $3.30): no person in any frame, a slow continuous push with no cut, no on-screen text, and the ending held on its final subject. One run, English, 480p, 16:9. It was "gallery practice only, never run here" until then

Practical consequence: both shapes this skill offers have now been run, and both at the durations the file leads with. What is risky about a first clip now is the script, not the format — specifically its sentence count, which the old budget ignored entirely and which costs about 0.7 seconds a boundary. A non-English script and any duration past 30 seconds are still unmeasured. Draft short and cheap, read the frames, listen once, then price the deliverable.

Where the core skill lives

Resolve once, before the first call:

bash

for d in ../ofox-video-core \
         ../ofoxai-skills-ofox-video-core \
         ~/.agents/skills/ofox-video-core \
         ~/.agents/skills/ofoxai-skills-ofox-video-core \
         ~/.claude/skills/ofox-video-core; do
  [ -f "$d/references/ofox-video.sh" ] && echo "$d" && break
done

Examples below are written as ../ofox-video-core/... (the skills.sh / ClawHub / npx ofox-skills layout, where a skill's directory is named after the skill). If the probe found a different directory — LobeHub unpacks each skill as ofoxai-skills-<name>, so the sibling there is ofoxai-skills-ofox-video-core — substitute it, in the ofox-video.sh commands and in the references/*.md links alike.

That ../ is relative to this skill's own directory, which is also where the probe has to run. From anywhere else nothing resolves — use the absolute path the probe printed (candidates 3–5 are absolute already), or, in a clone of this repo, skills/ofox-video-core/references/ofox-video.sh from the repo root.

Nothing found → the core skill isn't installed; see "If the script isn't found".

Before generating: the availability check

Run this once per session (not on every request):

bash

bash ../ofox-video-core/references/ofox-video.sh check

If it fails, follow ofox-video-core's guidance (install curl/jq, or get an OFOX_API_KEY at https://app.ofox.ai) — don't dead-end the conversation, and don't re-run this check on every subsequent request once it has passed.

check reports whether the key is present, not whether it is valid, and makes no network call. A failing check is not a stop sign: the idea selection, the script and the price can all be settled without a key — see "Pricing a job with no API key".

Two shapes, and what each costs you

	Presenter to camera (recommended)	Voiceover over footage
What is on screen	one person, chest-up, speaking	the thing being explained; the speaker is never seen
Evidence	six completed Ofox jobs built around photoreal people, text-to-video — one of them this skill's own 20s run, whose speech was transcribed against the script	one paid run, job 42d8b5c3 (2026-09-17, 30s, $3.30): no person in any frame, a slow continuous push with no cut, no invented lettering, and the ending held on its final subject
Best for	an opinion, an announcement, anything whose credibility comes from a person saying it	a product, an interface, a process, a physical object
Watch out for	the presenter is generated fresh every job and cannot be reused	a voice with nothing on screen to anchor it reads as stock footage with narration. Whether the model produces a disembodied narrator is no longer the open question — it did, for 30 seconds, once. Whether it does so reliably is
A real presenter's photo	not this skill — that is talking-head, and it needs a different model	—

Default to presenter-to-camera unless the subject is visual. When the subject is an interface or a physical object, say what the voiceover shape costs in certainty before choosing it.

Before writing the prompt: the brief

The shared rules — the three tiers, one round of at most four questions, the shape of a question, the "Let the AI decide" discipline, the order with the approval gate, the fallback without AskUserQuestion — are in ../ofox-video-core/references/creative-brief.md. This section adds only this scenario's question set.

Tier	Explainer axes
must-ask	which idea from the source the clip carries; whether the source is really there (a link nobody can open is not a source)
ask-if-open	presenter or voiceover, aspect ratio, register
never-ask	resolution, model, provider, audio on/off, the spoken language (it follows the source), duration once the word count has fixed it

The question set

#	Tier	header	Question	Options — first is recommended; "Let the AI decide" comes last where it appears, and never on a must-ask row	Ask when
1	must-ask	Idea	A clip this long holds about <N> spoken words in about <S> sentences, so it carries one idea rather than the article. Which one? (get <N> and <S> from the budget formula, not from memory — sentences cost about 0.7s each)	The two or three survivors of "Picking the idea", each shown as the sentence that would be spoken, with its word count; recommended = the most concrete. No "Let the AI decide" — it is their article. If they answer "you pick" in free text, take the most concrete, name it in the recap, and let the gate be the check	Always, unless the user already gave one sentence and asked for exactly that
2	ask-if-open	Shape	Who is on screen?	A presenter, to camera (recommended) — the shape this repo has actually run / Voiceover over footage of the thing — no speaker visible; better for an interface or an object, and untested here / Let the AI decide	The subject could go either way and the request doesn't say
3	ask-if-open	Aspect	Where will it be watched?	9:16 vertical (recommended) — feeds / 16:9 landscape — docs, a site, YouTube / 1:1 / Let the AI decide	No platform word and no ratio in the input
4	ask-if-open	Register	How should it sound?	Plain and direct (recommended) — a colleague telling you something useful / Warm and enthusiastic — a launch / Careful and precise — research, security, anything where overclaiming is the failure / Let the AI decide	The source's own register is ambiguous and the user gave no direction

If more than four are open, ask in this order: Idea, Shape, Aspect, Register. Duration is not a question — it falls out of the chosen idea's word count; it is a line in the recap and a row in the cost table.

Skip rows specific to this scenario

On top of the generic rows in creative-brief.md:

Input says…	Axis	Value
the language the source is written in	spoken language	that language, never asked — unless the user asks for a translation, which is then their words to approve
the user quotes one sentence and says "this, as a video"	Idea	settled; do not re-open it
"explain the new export feature" on a doc covering six features	Idea	narrow to that feature, then still pick one idea within it
"for LinkedIn", "for the docs site", "for the README"	Aspect	16:9
"for TikTok", "Reels", "Shorts"	Aspect	9:16
"show the app while I explain"	Shape	voiceover over footage — measured 2026-09-17 at 30s (job 42d8b5c3): no person, no cut, no invented lettering, and the ending held. One run, so still price a first one as a draft
"use my photo", "have me say it"	—	that is talking-head
"put the bullet points on screen"	—	not available from a description; see "On-screen text"

Every answer lands somewhere

Answer	Where it goes
Idea	the quoted LINE, and the word count that sets --duration
Shape	whether the prompt has a SPEAKER block or a SUBJECT block, and whether the voice is on camera or over
Aspect	--aspect-ratio
Register	the DELIVERY note and the micro-beats

The recap for this scenario

text

Brief
- Source: the v4 release post you pasted (1,100 words)
- Idea: "Version 4 stops dropping queries when the connection blips. If you wrapped
  every query in a retry, you can delete that now." — 22 words (you chose it from two)
- What this clip is NOT: a summary of the post. 9 seconds holds roughly 22 words
  in 2 sentences, so it carries this one idea and nothing else
- Shape: a presenter to camera (AI's pick)
- Duration: 9s — 22 words in 2 sentences is 22/3.56 + 0.7 = about 6.9s of speech,
  leaving room to open and to close
- Register: plain and direct (AI's pick)
- 9:16, 480p draft, audio on
- Note: the budget is measured on this model at 30 seconds (job `42d8b5c3`) — each
  sentence boundary costs about 0.7s, so a script with more sentences runs longer
  at the same word count. The delivery is still a roll, so treat the draft as the
  take you listen to

Then the full prompt, then the cost table approval-gate.md specifies, all in one message.

On-screen text — the thing users ask for that this cannot do

An explainer wants a title, three bullets and a logo. This API does not deliver them, and the reason is measured rather than stylistic: text rendered from a description comes back invented or garbled, repeatedly, across several jobs in this repo — while text approved on a still image and then attached as a frame is preserved, which is a different task.

So:

• Do not promise words on screen. Put the text items in AVOID (subtitles, captions, on-screen text, watermarks, logos) and keep lettered surfaces out of the set — the shared file's "Unwanted text is designed out of the set, not forbidden in the list" has the measurement, including that a negative list alone fails on a set full of signage.
• Captions and lower thirds go on in an editor afterwards, where they are free, correct and editable. This is worth saying early: it is usually good news.
• One route does exist and it costs the frame slot: prepare a title card as an image, read it at full size, and attach it with --frame-first-image. The clip then opens on exactly that card. Attaching a frame makes the output follow the image's shape (the script prints a NOTE: about adaptive), so crop the card to the delivery ratio first — crop, never pad. ofox-image-core's --target-aspect W:H does that and measures the real file.

Continuity across clips — the limit to state before a series is planned

If the user wants a three-part explainer with the same presenter, say this first: a photoreal presenter does not survive between jobs.

• Each generate is stateless; a person described in text is generated fresh every time.
• The usual fix — carry the previous clip's last frame into the next — is refused at submission on bytedance/seedance-2.5 when that frame holds a photoreal person (input_moderation_failed, measured, nothing billed).
• The words route (re-describing the previous frame in the prompt) brings back staging, wardrobe and props; it does not bring back a face.

What that leaves:

Want	Available
Three clips, same real person	not this skill. A portrait re-attached to each job is talking-head's route, and its own continuity is unmeasured
Three clips, same illustrated presenter	seedance-anime-drama — a non-photoreal character frame is accepted, which is exactly why that skill works
Three clips, no presenter	voiceover shape, with a consistent SCENE and STYLE block repeated word for word. Palette and setting carry; nothing else is guaranteed
Three clips, three different presenters	fine, and often the right answer — three ideas, three people, cut together

Each part is a separately billed job, and the cost table gets a row per part plus a total, per approval-gate.md → "Batches get an itemised table, not one total". Splitting is not a discount.

The prompt template

Vocabulary is not repeated here — delivery notes, camera and focus terms and the negative-list rows are in ../ofox-video-core/references/prompt-structure.md. An explainer is a single shot with performance beats inside it, so the shared file's "Short prompts (10 seconds or less)" shape applies even above 10 seconds: no shot manifest, no cut list.

Slots in <angle brackets>; optional lines in [square brackets].

Presenter to camera

text

One continuous shot, <T> seconds, fixed camera, no cuts.
SPEAKER: <age range, build, hair, top with colour and material>, <one bearing word — relaxed, precise>. <No name; this person exists for one clip.>
SCENE: <a plain setting that does not compete: a home study, a quiet office, a plain wall>. <One light source and its direction.> <Nothing in the background carrying letters.>
FRAMING: chest-up medium close-up, <fixed camera | a faint breathing handheld>, background softly out of focus; real mirrorless texture, slight sensor noise, real skin texture, no smoothing.

<Speaker> faces the camera and says, <delivery: plain and direct, unhurried | warm | careful and precise>: "<the chosen idea, verbatim, in the language to be spoken>"
0–<a>s: <eye contact, one natural blink>. <a>–<b>s: on "<the key word>", <one gesture>. <b>–<c>s: <stillness>. <c>–<T>s: after "<last word>", <the ending: lips close, half-second pause, the smallest nod>.

SOUND: <room tone>, no music. Speech in <language>, mouth shape matched to it.
CONSISTENCY: face, hair, <clothing items>, background and light direction identical from the first frame to the last.
AVOID: subtitles, captions, on-screen text, watermarks, logos, diagrams, charts; a second person, a cutaway, an interview setup; music, score, soundtrack, instrumental, humming, singing; presenter cadence, theatrical over-acting, wild gesturing; skin smoothing, beauty filter, plastic skin, CGI look; camera movement, zooms, cuts.

Voiceover over footage

text

One continuous shot, <T> seconds, <slow push | slow drift>, no cuts. No person on screen at any point.
SUBJECT: <what is being explained, described the way a camera sees it: a laptop on a desk with a dashboard open, a hand-held device on a bench, a machine in a workshop>.
SCENE: <where it sits, one light source and its direction>. <Nothing in frame carrying letters.>

A single voice, off-screen, says, <delivery>: "<the chosen idea, verbatim, in the language to be spoken>" — no speaker is ever visible.
0–<a>s: <what the camera is looking at>. <a>–<b>s: <what changes, tied to the words being said>. <b>–<T>s: <the close>.

SOUND: <room tone>, <one or two sounds tied to what is visible>, no music. Narration in <language>.
AVOID: subtitles, captions, on-screen text, watermarks, logos; a presenter, a face, hands entering frame, an interview setup; music, score, soundtrack, instrumental, humming, singing; cuts, zooms, whip pans; CGI look, plastic surfaces.

Five notes on both shapes:

• The idea is quoted verbatim and never paraphrased. Put the full spoken sentence inside the prompt shown at the approval gate, so the user reads exactly what will be said. A line silently rewritten is the most expensive thing that can go wrong here, because it looks fine until the clip plays.
• The spoken language follows the line's language. Write the user's own language in; translating to match the English examples buys them an English-dubbed clip they find out about after paying.
• No music, ever. Not taste: a prompt asking this model for a scored cue came back output_moderation_failed on audio copyright in this repo, unbilled. Name the music words in AVOID as well as writing no music — that is the pair of blocks the two clean runs used. A track goes on in an editor.
• No text, per the section above, and in the voiceover shape that extends to the subject: an interface full of legible labels is a set full of lettered surfaces, which is exactly where invented lettering shows up. Frame it tighter, or attach a real screenshot as the first frame and let the lock hold the words.
• --generate-audio stays at the server default (true). The speech is the deliverable.

Worked example — 9 seconds, 22 words, presenter to camera

This has not been generated as written. It is the template filled in, carrying the release-post idea chosen above.

text

One continuous shot, 9 seconds, fixed camera, no cuts.
SPEAKER: a man in his 30s, average build, short dark hair, a plain charcoal crew-neck sweater; relaxed, precise.
SCENE: a quiet home office; a plain pale wall behind him with nothing on it. The only light is a window to the front-left, soft and slightly cool, falling off across the far side of his face.
FRAMING: chest-up medium close-up, fixed camera, background softly out of focus; real mirrorless texture, slight sensor noise, real skin texture, no smoothing.

He faces the camera and says, plain and direct, unhurried: "Version 4 stops dropping queries when the connection blips. If you wrapped every query in a retry, you can delete that now."
0-2s: he looks straight into the lens, one natural blink. 2-5s: on "dropping queries" a single small open-palm beat, low in frame, and the hand leaves again. 5-8s: stillness; the eyebrows lift slightly on "retry". 8-9s: after "now" the lips close, one slow blink, the smallest nod, and the shot holds.

SOUND: quiet room tone, a little distant traffic. No music. Speech in English, mouth shape matched to it.
CONSISTENCY: face, short dark hair, charcoal crew-neck sweater, the pale wall and the light direction identical from the first frame to the last.
AVOID: subtitles, captions, on-screen text, watermarks, logos, diagrams, charts; a second person, a cutaway, an interview setup; music, score, soundtrack, instrumental, humming, singing; presenter cadence, theatrical over-acting, wild gesturing; skin smoothing, beauty filter, plastic skin, CGI look; camera movement, zooms, cuts.

The duration was derived from the script rather than the other way round: 22 words at 3.56 a second is 6.2 seconds of speaking, plus one sentence boundary at 0.7s, giving a 6.9-second span — then room to open and to close, rounded up to 9. Note that the sentence count is in that arithmetic. Break the same 22 words into four short sentences and the span grows by about 1.4 seconds, which is most of the headroom. If a script is running long, joining sentences buys back time that cutting words does not.

It is also why a 22-word idea gets a 9-second clip and not a 15-second one with six seconds of nothing in it: on a per-second bill, the script decides what you pay for.

Recommended defaults

Parameter	Default	Why
--model	the script's own default, bytedance/seedance-2.5 — unless the user named one, which always wins	no portrait is attached here, so nothing forces a different model, and this repo's spoken-dialogue runs are all on it. See "Choosing a model"
--duration	derived from the chosen idea with words/3.56 + 0.7 x (sentences − 1), plus room to open and close, then clamped to the model's range — which ofox-video.sh models prints. For Chinese or Japanese the only figure available is still 4 characters a second	the script decides the length; a default that ignores it produces rushed speech. The English formula is measured on this model at 30 seconds (job 42d8b5c3): 3.56 w/s while speaking and ~0.7s at each of the script's 7 sentence boundaries, predicting 27.4s against a delivered 28.13s. ⚠️ Count sentences as well as words — that term is what the old "3 words a second" flat rate left out, and it is why "about ninety words in thirty seconds" did not fit. The CJK figure is still gallery-derived and untested
--resolution	draft at the model's cheapest tier, deliver one tier up	a face at the cheapest tier is where lip and eye detail goes first, so read the draft's frames rather than shipping it
--aspect-ratio	9:16 unless the brief or the platform said otherwise; not passed if a title card is attached as a frame	short explainers are watched in feeds
--generate-audio	leave at the server default (true)	the speech is the deliverable
--seed	let the script roll one and keep it	printed as SEED and written to the .json sidecar. It does not reproduce a take — measured, an identical request on a fixed seed came back a visibly different clip — so a re-render is another roll aimed at the same shot. Say that before the user pays for one
--frame-first-image	unset, unless a prepared title card or screenshot is the opening frame	the only route to correct lettering; it also fixes the clip's shape to the image's
--real-person	leave unset	nothing in this skill needs it — the presenter is written in text, and text-generated people are not what the refusal is about. true is Ofox's privacy-preserving preprocessing path for authorised real-person reference images, measured lifting seedance-2.5's refusal on 2026-09-16; it is an authorisation route, never a way past the check, and a skill whose presenter comes from a photo is talking-head, not this one. See api-params.md → "--real-person true lifts that refusal on 2.5"

Choosing a model

The model stays never-ask — the agent doesn't raise it. But never-ask is not "never listen": if the user names a model id or a shorthand, use it.

Model ids, prices, resolutions, durations and aspect ratios are deliberately not tabulated in this file. They are catalog facts, they change, and this repo has recorded defects that trace to a hardcoded copy of somebody else's value table. Read them live, free, with no API key:

bash

bash ../ofox-video-core/references/ofox-video.sh models             # every model, its tiers and ranges
bash ../ofox-video-core/references/ofox-video.sh providers MODEL    # that model's per-resolution rates

providers with no model argument prints the flagship's matrix, not the catalog — pass the id you actually mean. The rate models shows is the one at each model's own default resolution, which differs between models, so it ranks rather than quotes. The number you put in front of a user comes from generate --dry-run at the parameters you are about to send.

Two things worth saying to a user who is choosing: a cheaper model is a different look, not just a smaller bill — and it is faces that lose most. And moderation policy is per-model, so a prompt refused on one model can be accepted on another.

Before you spend: the approval gate

Never submit a paid job until the user has seen a cost table and said yes. The rule, the required columns and where the numbers must come from are written down once for every Ofox skill in this repo: ../ofox-video-core/references/approval-gate.md.

Get the numbers from --dry-run, which validates everything and prints the estimate without sending a request:

bash

bash ../ofox-video-core/references/ofox-video.sh generate --dry-run \
  --prompt "..." --duration 9 --resolution 480p --aspect-ratio 9:16 \
  --out-dir /absolute/path/to/out

Relay the Estimated cost: line it prints — never a number of your own — then wait for a yes, then re-run the identical command with --dry-run removed. The estimate a real run prints comes microseconds before the request goes out, too late to relay. Pass the same --out-dir to both.

Three things belong in that message beyond the table:

• the chosen idea, quoted in full, as the words that will be said;
• one line saying what the clip is not — a summary of the source — so the expectation is corrected before the money moves, not after;
• one line saying which parts are measured and which are a first attempt — the word budget is measured on this model at 20 seconds and 480p; the voiceover shape, a non-English script and anything longer are not.

This skill has exactly one cost anchor, and it anchors one point rather than a curve: 20 seconds at 480p on bytedance/seedance-2.5, text-to-video, billed 2 dollars 20 (job edef379e). Another duration or resolution is a different number, so the --dry-run figure at the parameters you are about to send is still the only one to put in front of anyone.

Afterwards the actual bill is VIDEO_COST from the finished job. Report it as money, not as the raw ten-decimal string.

Several takes

Delivery is a roll, and this genre is judged on whether the person sounds like they mean it. batch prices the whole set up front, waits concurrently, and tiles a contact sheet:

bash

bash ../ofox-video-core/references/ofox-video.sh batch --dry-run \
  --prompt "..." --takes 3 --duration 9 --resolution 480p \
  --aspect-ratio 9:16 --out-dir /absolute/path/to/out

Quote BATCH_COST_TOTAL, not BATCH_COST_PER_TAKE, and give the takes a row each. Hand over the CONTACT_SHEET path on its own line, then the take paths beneath it. A contact sheet cannot tell you how a take sounds — it is frames. Listen to one before promoting it.

If the user wants several cheap vertical drafts as the deliverable rather than one clip, shorts-reels owns that ladder. The two compose: pick the idea and write the prompt here, run the set there.

Pricing a job with no API key

models, providers and generate --dry-run all work with OFOX_API_KEY unset. So when a user hasn't signed up yet, quote the job first and let them decide whether it's worth registering — don't open by sending them to a signup form.

If the script isn't found

text

bash: ../ofox-video-core/references/ofox-video.sh: No such file or directory

Nothing is broken — this skill delegates all execution to ofox-video-core and reaches it by relative path, and that path just missed. Two different situations wear this message, so run the probe in "Where the core skill lives" before deciding which:

• The probe printed a directory — the core is installed and only the directory name was wrong, which is the normal LobeHub case (ofoxai-skills-ofox-video-core). Re-run against what the probe printed.
• The probe printed nothing — ofox-video-core really is absent, and installing it is the user's call to make, not yours: an install writes outside this working directory, so hand over the command and let them run it rather than running it for them. Which command depends on the installer they already have — skills.sh is npx skills add ofoxai/skills --skill ofox-video-core, which asks for that one skill and answers none of the agent, scope or confirmation questions on the user's behalf; this repo's own wrapper is npx ofox-skills ofox-video-core, the same install with all three answered in advance (every agent, user-level, no prompts); on LobeHub or ClawHub, install ofox-video-core from the same publisher. Ask for the one skill that is missing rather than the whole repo, and give all three routes — pointing a LobeHub user at the skills.sh line alone reads as "abandon your installer", which isn't the advice.

Either way, name the missing skill and where it was expected rather than relaying the raw path error, which names neither.

A broken link to a shared reference has the same two causes. This skill degrades gracefully: the selection procedure, the question set, the templates, the word budget and the defaults are all written out here. What is out of reach is the detail behind them — the full delivery and camera vocabulary, the gallery cases behind the word rates, and the exact wording of the spend gate, which stays mandatory either way.

Exit codes worth knowing

Full table in ../ofox-video-core/SKILL.md. The ones that come up:

Code	Meaning	What to do
1	Parameter rejected locally, no network call, nothing billed	Fix the flag and retry freely
2	Environment problem — curl/jq missing, or no OFOX_API_KEY	Ask the user to fix it; check reports the same
3	API rejected it, or the job ended failed/cancelled/expired	Read the mapped message; a rejected create was not billed
4	Timed out waiting — the job is still running and billable	poll JOB_ID, never re-run generate
5	Ambiguous network failure on create	Do not retry blindly; check https://app.ofox.ai first
6	--out-dir unusable	Fix the path; if it happened after a create, poll JOB_ID

How long to tell the user it will take

generate blocks while it polls, up to --max-wait (default 540s). A short low-resolution clip is usually one to three minutes. Say so before starting, so the wait isn't silent.

If your tool call can't stay open that long, use create (submits and returns a job id in seconds) followed by poll. That way a timeout can never strand a job whose id you never saw. For batch, the worst case is takes x max-wait.

Where the file lands

Always pass --out-dir, and make it an absolute path. Without it the script writes to the current working directory — which, given that the examples here run from this skill's own directory, would drop the user's video inside an installed skill. Relay the absolute VIDEO_PATH the script prints, on its own line.

Pass --name too, named after the idea rather than left for the script to guess from the prompt's opening words, which here describe a shot length. The clip lands as <name>-<short job id>.mp4 with a .json sidecar holding the full job id, the prompt, the seed and the real cost.

Generating

bash

bash ../ofox-video-core/references/ofox-video.sh generate \
  --prompt "<the explainer prompt built above>" \
  --name "<short idea name, e.g. v4 retry removal>" \
  --duration 9 \
  --resolution 480p \
  --aspect-ratio 9:16 \
  --out-dir /absolute/path/to/out

Drop --aspect-ratio if a title card or screenshot is attached as the first frame — the clip then follows the image's shape.

This one call validates the parameters, submits the job, polls to completion, downloads the mp4, and prints STATUS, JOB_ID, VIDEO_PATH, VIDEO_SECONDS, SEED and VIDEO_COST. Report the actual values from that output — never the estimate, and never a path or cost you didn't see the script print. Do not re-implement any of the request, poll or download logic here.

After it lands: what to actually check

Three things, before calling it done. None of them is STATUS completed.

1. Were all the words said? Listen once and count against the script. Rushed, clipped or dropped endings mean the clip was over budget; the fix is a longer clip or fewer words, never a faster delivery. The one run measured here lost nothing, but that is one take on one script — delivery is a roll, so check it rather than assuming this one.
2. Is the idea still the idea? A generated delivery can land emphasis somewhere that changes the meaning. Read the source's claim against what you just heard.
3. Did any lettering get invented? Check a few frames for signage, captions or a logo nobody asked for.

Report what you checked, not just that it finished.

Common failure modes and fixes

Symptom	Cause	Fix
The user expected the article summarised and got one idea	The expectation was never corrected	Correct it before the cost table, in the recap's "What this clip is NOT" line. After the fact, the only remedy is another job
The speech is rushed, garbled, or the last words are missing	More script than the clip holds — usually a summary squeezed to fit. ⚠️ Check the sentence count as well as the word count: each boundary costs about 0.7s, so a script that passed a words-only check can still overrun	Fewer words, or the same words in fewer sentences, or a longer clip inside the model's range. Never compress the delivery. New prompt, new cost table
The clip ends mid-sentence	Same cause, plus no written ending beat	Re-budget with words/3.56 + 0.7 x (sentences − 1) and write the final beat explicitly. If the word count already looked safe, count the sentences — each boundary costs about 0.7s, and joining two short sentences buys that back without losing content
The voice speaks the wrong language	The line was translated on the way into the prompt	Put the source's own words in, untouched. The line's language decides the voice's language
Invented captions, a garbled title, a logo nobody asked for	Text rendered from a description is the classic failure, and a negative list alone does not hold on a lettered set	Keep the text items in AVOID and compose lettered surfaces out of the frame. Real captions go on in an editor; a title card has to be a prepared image attached as the first frame
A music bed nobody asked for	--generate-audio true and a prompt that didn't exclude music	Keep no music in SOUND and the music words in AVOID
Exit 3, output_moderation_failed mentioning audio copyright	The prompt asked for music	Rewrite SOUND as room tone only and re-run — a new request, safe immediately, nothing was billed
Exit 3, input_moderation_failed on create	An attached frame contains a photoreal person — refused at submission on this model, nothing billed	Attach a card, a screenshot or an object instead and write the person in text; or move to talking-head, which runs a different model for exactly this reason
Part 2's presenter is a different person from part 1's	Every job generates the presenter fresh, and nothing in this skill's route carries a face between jobs — the words route brings back staging, not a face	See "Continuity across clips". Choose one of the four available shapes rather than re-rolling
The presenter gestures like a newsreader	No delivery note, or too many gestures written	One gesture per beat at most, and a plain register in the DELIVERY note. New prompt, new cost table
The voiceover clip has a person in it anyway	A subject description that implies a user	No person on screen at any point in the first sentence, and a face and hands in AVOID. Untested shape — draft it cheaply
Exit 4, timed out waiting	Still running upstream, not failed	poll JOB_ID with the id printed before the timeout; never re-run generate
Exit 5, ambiguous network failure on create	No HTTP response at all — can't tell whether a job exists	Don't guess or retry; tell the user to check https://app.ofox.ai

When NOT to use

• The user has a portrait and finished words — talking-head. The split is about where the labour is: there the words already exist and a specific face has to say them; here the words have to be found in a source and no particular face is required. That skill also runs a different model, because bytedance/seedance-2.5 refuses a real person's photo at submission.
• A scene between people — seedance-short-drama. The boundary is not "is there speech", it is who is being addressed: characters talking to each other is that skill, one voice addressing the viewer is this one. Short drama also owns shot lists, cuts and stage direction, none of which belongs in an explainer.
• A brand or product ad — seedance-ad-creative. An explainer that exists to sell is an ad, and that skill has the beat structure for it.
• A handheld creator clip — ugc-ads, even when the creator is explaining something. That skill inverts the polish this one defaults to.
• Several cheap vertical drafts as the deliverable — shorts-reels owns that ladder. Write the prompt here, run the set there.
• The user wants the article summarised. That is a writing task and it is free. Offer it, and let them decide whether a clip is still wanted afterwards.
• Anything needing slides, diagrams, charts or readable bullets. A narrated deck does that properly, costs nothing, and can be corrected. Say so before quoting a job that cannot deliver a legible word.
• A three-minute explainer. One job is one clip, and a series of them has the continuity limit above. Past two or three parts, a screen recording with a voiceover is the better product.