caption-animation
Skill11 starsChanged 4 months agoMITView on GitHub
This skill should be used when the user asks to "add animated captions", "make TikTok captions", "karaoke captions", "word-by-word subtitles", "auto subtitles", "highlight the active word", "burn in captions to a video", "sync captions to a voiceover/narration", or "turn an SRT/transcript into animated text". Covers word-level timing from Whisper, per-word pop/scale-in, active-word highlight, 9:16 safe-area placement, readable type, and burn-in vs sidecar SRT/VTT.
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 50
If only sentence-level cues exist, re-transcribe for word timing — do not interpolate.
- Distinctive: line 116
Place captions in the center band — not pinned to the very bottom, where the platform UI (username, audio, buttons) lives.
- Very specific: line 166
Use npx remotion compositions to read durationInFrames/fps and pick the active-word + end frames.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Caption Animation
Turn a transcript or voiceover into word-timed, scroll-stopping captions: each word pops in on the syllable, the active word highlights, and the text stays glued to the narration. Build the kind of captions that drive watch-time on TikTok, Reels, and Shorts — readable, on-beat, and inside the safe area.
When to use
- Word-by-word or karaoke captions on short-form vertical video (9:16).
- Burning open captions onto a voiceover/narration track from a transcript.
- Turning a Whisper/SRT transcript into animated text in Remotion or on the web.
- Restyling auto-generated subtitles into a branded, "Hormozi-style" reveal.
The pipeline
| Stage | Job | Tool |
| Transcribe | Audio → word-level timestamps | Whisper (@remotion/install-whisper-cpp), AssemblyAI |
| Normalize | → { text, startMs, endMs }[] tokens | @remotion/captions Caption type |
| Page | Group words into 1–4 word "pages" | createTikTokStyleCaptions() |
| Animate | Per-word pop + active-word highlight | Remotion spring() / CSS |
| Place | Safe-area, readable type | layout rules below |
| Export | Burn-in (MP4) and/or sidecar SRT/VTT | Remotion render / file emit |
Two non-negotiable rules
- Word-level timing, not line-level. Karaoke reads as magic only when each word lands on the syllable. Always transcribe to word timestamps; never fake them by splitting a line evenly over its duration — drift is instantly visible.
- Readability beats style. Captions are read on a phone, in sunlight, muted. Bold sans-serif, heavy stroke or shadow, high contrast first; decoration second. A caption nobody can read is decoration, not a caption.
Word timing from a transcript
Whisper emits word-level timestamps directly. Normalize every source into one flat token shape so the renderer never cares where the words came from:
// Caption token — the one shape everything downstream consumes
type Token = { text: string; startMs: number; endMs: number };
// Parse an SRT cue block "00:00:01,200 --> 00:00:01,640" into ms
const toMs = (t: string) => {
const [h, m, rest] = t.split(":");
const [s, ms] = rest.split(",");
return ((+h * 60 + +m) * 60 + +s) * 1000 + +ms;
};If only sentence-level cues exist, re-transcribe for word timing — do not interpolate. Whisper's medium.en is ~2x faster than large and accurate enough for clean voice audio.
Per-word pop-in (Remotion)
Drive each word's scale and opacity off a spring anchored to its own startMs. The micro-overshoot is what makes it feel "alive".
import { useCurrentFrame, useVideoConfig, spring, interpolate } from "remotion";
const Word: React.FC<{ token: Token; active: boolean }> = ({ token, active }) => {
const frame = useCurrentFrame();
const { fps } = useVideoConfig();
const enter = (token.startMs / 1000) * fps; // word's own entrance frame
const p = spring({ frame: frame - enter, fps, config: { damping: 12, mass: 0.6 } });
const scale = interpolate(p, [0, 1], [0.6, 1]); // pop from 60% → 100% (overshoots)
return (
<span style={{
display: "inline-block",
transform: `scale(${scale})`,
opacity: interpolate(p, [0, 1], [0, 1]),
color: active ? "#FFE45E" : "#FFFFFF", // active-word highlight
transition: "color 80ms linear",
}}>{token.text} </span>
);
};Compute active by testing frame against each token's [startMs, endMs]. Keep the highlight a single accent color or a filled "box" behind the live word — never animate every word's color at once.
Pages, not walls of text
Show 1–4 words at a time. Use Remotion's createTikTokStyleCaptions() (or group manually) and tune combineTokensWithinMilliseconds: ~200–500ms for true word-by-word, ~1000–1500ms for short readable phrases.
import { createTikTokStyleCaptions } from "@remotion/captions";
const { pages } = createTikTokStyleCaptions({
captions, combineTokensWithinMilliseconds: 1200, // ~2–3 words per page
});Web/CSS pop (no Remotion)
For a DOM/live player, give each word its own animation-delay equal to startMs:
.word { display:inline-block; opacity:0; animation: pop .26s cubic-bezier(.34,1.56,.64,1) forwards; }
@keyframes pop { from { opacity:0; transform:translateY(.18em) scale(.7) } to { opacity:1; transform:none } }
.word.active { color:#FFE45E; }words.forEach(w => { const el = mk(w.text); el.style.animationDelay = `${w.startMs}ms`; track.append(el); });Readable type and safe-area placement (9:16, 1080×1920)
| Property | Value | Why |
| Font | Bold/ExtraBold sans (Montserrat, Inter, Helvetica) | Reads on small, busy screens |
| Size | 56–80px (≈8% of frame height), min 45px | Legible muted on a phone |
| Stroke | 2–6px solid black outline | Survives any background |
| Shadow | Soft drop shadow as backup to stroke | Separation on bright frames |
| Case | Uppercase or sentence; high contrast fill | Punch + scannability |
| Vertical pos | Center band, ~62–70% down | Above the UI, below the action |
| Bottom safe | Keep clear of bottom ~280px / 15% | Avoids caption/CTA/audio UI |
| Side safe | Keep within center 80% width | Avoids right-rail icons |
Place captions in the center band — not pinned to the very bottom, where the platform UI (username, audio, buttons) lives. Pad text to a max of ~2 lines.
Sync to a voiceover / narration
The transcript already carries the timing of the exact audio. Lay that same audio under the composition and keep timestamps in the audio's timebase — captions and voice stay locked with zero manual nudging. If the VO is re-recorded, re-transcribe; never hand-shift offsets.
Burn-in vs sidecar SRT/VTT
| Burn-in (open) | Sidecar SRT/VTT (closed) | |
| Where | Pixels in the MP4 | Separate .srt/.vtt file |
| Social (TikTok/Reels) | Required — guaranteed, styleable | Often ignored by the platform |
| Accessibility (ADA/WCAG) | Does not satisfy alone | Required (toggleable) |
| Best practice | Burn animated captions for social | Also ship a sidecar for the web/SEO |
Emit both: burn the animated captions for social, and write a plain SRT/VTT from the same tokens for accessible/SEO playback.
Output checklist
- Word-level timestamps (real, from transcription) — no even-split fakery.
- Per-word pop with micro-overshoot; one accent color for the active word.
- 1–4 words per page; never a wall of text.
- Bold sans, 56–80px, 2–6px stroke + shadow, high contrast.
- Center band, clear of bottom ~280px and side rails.
- Audio laid under composition; timestamps in the audio timebase.
- Ship burn-in for social and a sidecar SRT/VTT for accessibility.
Deliver & verify (rendered stills → MP4)
Packaged helper (
scripts/): tile your stills withscripts/contact-sheet.sh sheet.png f-hook.png f-mid.png f-end.png, then assert the encode withscripts/probe-mp4.sh out.mp4 [WxH] [fps]. Seescripts/README.md.
Captions ship as a Remotion composition (<Composition> + zod schema + defaultProps) — all word motion frame-driven off useCurrentFrame(), never Date.now() / Math.random() / timers. Deliverable = out/*.mp4 (burned-in) + the project + the sidecar SRT/VTT. 9:16 vertical (1080×1920) is the default.
Verify loop — render stills → inspect → encode. Word timing is the thing that breaks; check it at exact frames before you spend an encode.
# Stills at start / a sampled active-word frame / end — WITH SHIPPED PROPS (real tokens + audio)
npx remotion still Captions out/f-start.png --frame=0 --props='{"captionsSrc":"vo.json"}'
npx remotion still Captions out/f-mid.png --frame=90 --props='{"captionsSrc":"vo.json"}'
npx remotion still Captions out/f-end.png --frame=N --props='{"captionsSrc":"vo.json"}' # N = durationInFrames-1
# Inspect each PNG:
# - the word highlighted at frame 90 is the word whose [startMs,endMs] contains 90/fps (no drift)
# - burn-in legible: bold sans, stroke+shadow holds, no clipping
# - 9:16 safe area: caption sits in the center band, clear of top ~12% and bottom ~20-35% (captions/CTA/audio UI) and the right action rail
npx remotion render Captions out/captions.mp4 --props='{"captionsSrc":"vo.json"}' # encode once stills are right
npx remotion render Captions out/demo.gif --codec=gif # README proof clipUse npx remotion compositions to read durationInFrames/fps and pick the active-word + end frames.
Before you finish:
- Stills render cleanly at frame 0, a mid active-word frame, and last — no missing font/audio.
- The correct word is highlighted at the sampled frame (frame/fps lands inside its token); no even-split fakery.
- Burn-in is legible (stroke+shadow) and the caption is fully inside the 9:16 safe area at every checked frame.
- Frame-driven only — no
Date.now()/Math.random()/ timers. - Shipped props (real tokens, not just
defaultProps) render correctly; MP4 + sidecar SRT/VTT emitted, GIF optional.
Reference files
references/word-timed-captions.md— end-to-end build: Whisper transcription and theCaptiontype, a full SRT parser, Remotion word-timed component with active-highlight, manual paging, an SRT/VTT emitter, per-platform safe-area maps, and a readable-type spec sheet.
Other versions1 project uses a version of this.
Word for word · 1
- willlee1995/skills★ 1100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository3 other files it gives its agents.
- countdown-videoSkill
- lower-thirdsSkill
- short-form-videoSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

