Captions and talking-head footage

The first two rides built a video from nothing and the third built one from a diff. This one starts from footage you already have — a talking-head clip — and adds a layer on top without touching the shot itself.

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Your first win

One prompt to /embedded-captions, pointed at an existing clip, is enough for a finished captioned video — no technique required yet. 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.

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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. 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.

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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.

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The knobs that matter

What you can already steer from the prompt, before you’ve learned any technique. 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.

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Variants

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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.

Next: Music videos and slideshows — swap footage for a soundtrack, or slides, and let the beat or the deck set the pace.