Skip to main content

​
Two things you can add to a talking head

Both workflows take an existing talking-head / interview / podcast clip and add a layer on top. Neither edits the footage — no trims, no recolor, no reframe, no reorder. The clip plays untouched underneath; you’re choosing what rides on top of it.
You wantRouteWhat it adds
The spoken words as readable text/embedded-captionsCaptions / subtitles — a rail, with earned climax embeds
Designed on-screen graphics synced to the talk/talking-head-recutOverlay cards — titles, lower-thirds, data callouts, quotes, PiP
If the words themselves need to read, you want captions. If you want a produced look — kinetic titles, a stat callout, a pull-quote card, the speaker shrunk into a corner while a chart fills the frame — you want overlay cards. When it’s genuinely both, caption first, then package; they’re siblings, not substitutes. /embedded-captions runs locally end to end — it transcribes and mattes the subject itself, no API key — and needs a single-subject clip. Multi-speaker clips or hard cuts get split per shot or refused, because the matte is one person.

​
Base prompt — captions

Captions route by identity, not by mode. You pick one look from the catalog; the engine behind it is a lookup detail you never have to name. The default is a clean verbatim rail — anchor — with the occasional peak word composited behind the subject.
/embedded-captions Add captions to ./interview.mp4. Use the anchor identity — clean verbatim rail carrying the spoken words, readable lower-third. Promote the single hardest-hitting word to an embed behind the speaker; highlight one key word in each rail line. Keep the source aspect ratio. Footage stays untouched.
Rendered from the prompt above on generated avatar footage, unedited — one earned embed behind the speaker, everything else on the rail. The rail carries most of the text; an embed is the scarce, earned peak — one big word matted behind the subject at the climax, never every line. Embedding the whole transcript is the most common mistake this skill guards against.

​
Base prompt — overlay cards

/talking-head-recut Package ./founder-clip.mp4 with designed graphic overlay cards synced to the transcript. 9:16 portrait, warm-paper style. Open with a fullscreen kicker + title hook, drop a lower-third when she names the company, a data callout card counting up the “200+ teams / $1.2M ARR” stat, and a pull-quote card for the strongest line. Speaker stays full-bleed under the cards; shrink her into a corner PiP while the data card holds. The clip plays untouched underneath.
You describe the cards — their content, timing, and how the speaker shares the canvas with them (full-bleed, split, PiP, or glass overlay). The skill designs and writes each card; there’s no fixed archetype list, so the overlays follow what the transcript actually says.

​
Variants

/embedded-captions Cinematic captions on ./poem.mp4 — no rail, hero typography composited behind the speaker, words accumulating as a column. Use the editorial identity (lowercase-italic hero). One apex word per thought, air between them. 4:5. Never grade the footage.
Column-flow identities drop the rail and make everything embed-style — reach for them on poetic / social / “cinematic” asks where mood beats strict readability, never on an explainer where the words must read.
/embedded-captions Add verbatim captions to ./outdoor-vlog.mp4. It’s a bright daylight scene, so use the ink identity — near-black type printed onto the surface — not a light-on-bright look that washes out. Keep it a readable rail. 16:9.
Screen-blend cream looks wash out over bright backdrops (luminance > ~180); ink is built for bright surfaces. Match the identity to the scene rather than asking the engine to recolor a look.
/embedded-captions Bring the energy on ./hype-clip.mp4 — I want the captions to hit hard. Use the ordnance identity: a stamped verbatim rail with a detonation apex. Rail carries the verbatim; the payoff line is the setpiece. 9:16.
Themed identities (ordnance, terminal, stomp, neonsign, stardust, …) are the answer to “make it explode / 特效 / like AE did it”. Theme mode is the one place a register-gated reaction beat may touch the frame — applied after the matte composite so subject, text, and plate move as one — but the a-roll is still never graded.
/talking-head-recut Recut ./analyst-interview.mp4 as a 16:9 explainer with a clinical style. Split layout: speaker on the right, data cards on the left. Cards for each claim — a count-up for the headline number, a swiss-grid comparison for the two options, a terminal-style callout for the technical bit. Auto-pace the card count for a 5-minute clip. Footage untouched.
Layout (split / stack / pip / overlay) sets how speaker and cards share the canvas; card count auto-infers from duration and information density, with a floor of five so even a short clip has rhythm.

​
The knobs that matter

Identity and tone (captions). One identity picks the entire look — surface, palette, motion, climax behavior. Route by content: explainer / interview / must-read words → a rail-carrying identity, with anchor the conservative default where every word has to read; poetic / social / cinematic → a column-flow identity by register (editorial, cream, loud, neon); “炸 / 特效 / VFX” → a themed identity (ordnance, terminal, stomp). Unsure → anchor: the words read and the scene stays safe. Don’t ask for “Standard vs Cinematic vs Theme” — those are engine names; name the identity. Verbatim rail vs climax embed. The rail is the default and carries most of the text. An embed is a promotion — one peak word matted behind the subject, scarce and spaced (roughly one per beat, never two co-visible, at most one apex). Tell the skill which lines earn the embed; leave the rest on the rail. Style, layout, and canvas (recut). Pick a style group (warm-paper / clinical / experimental), a layout (split / stack / pip / overlay), and a canvas ratio; the video frame follows from layout × style. The recommended ratio matches the source, but you choose — 16:9 for desktop / YouTube, 9:16 for Reels / Shorts, 4:5 for feed. Keyword highlighting. On the caption rail, a punch word can carry an inline emphasis — an accent-color or active-word pop — without leaving the rail. Ask for “highlight the key word in each line” and it stays readable.

​
Failure modes

Asking for footage edits. Both skills add a layer and leave the a-roll exactly as shot. Trimming, speeding up, recoloring, reframing, or reordering is NLE editing and out of scope — captions and cards are the only additions.
  • ❌ add captions and trim the dead air at the start, and warm up the color to match my brand
  • ✅ add captions; leave the footage untouched — do the trim / grade in an editor first, then bring the finished clip here.
Embedding every word. On a talking head the rail is the verbatim default; matting every caption behind the subject buries the words and spends the climax on nothing.
  • ❌ composite every caption behind the speaker for a cinematic look (on an explainer)
  • ✅ verbatim rail; promote only the two payoff lines to an embed
Multi-subject clips. The caption matte is one person; two speakers or hard cuts flicker or get refused.
  • ❌ caption this two-person podcast in one pass
  • ✅ split the clip per shot / per speaker first, then caption each — or use a single-subject cut.
For the beat-timestamped skeleton these prompts share, see Prompt anatomy; for adjectives that map to motion and emphasis settings, Vocabulary. To build a video from scratch instead of dressing existing footage, start at the router in /hyperframes.