iart-ai/tiktok-video-skills

caption-animation

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".

Trending #6936 First seen Jun 22, 2026

Installation

$ npx skills add iart-ai/tiktok-video-skills --skill caption-animation

Summary

  • 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.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 9
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version0.1.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 9,937 B
  • docs SUMMARY.md 490 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 511 installs

SKILL.md

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

  1. 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.
  2. 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}&nbsp;</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 with scripts/contact-sheet.sh sheet.png f-hook.png f-mid.png f-end.png, then assert the encode with scripts/probe-mp4.sh out.mp4 [WxH] [fps]. See scripts/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 clip

Use npx remotion compositions to read durationInFrames/fps and pick the active-word + end frames.

Before you finish:

  1. Stills render cleanly at frame 0, a mid active-word frame, and last — no missing font/audio.
  2. The correct word is highlighted at the sampled frame (frame/fps lands inside its token); no even-split fakery.
  3. Burn-in is legible (stroke+shadow) and the caption is fully inside the 9:16 safe area at every checked frame.
  4. Frame-driven only — no Date.now() / Math.random() / timers.
  5. 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 the Caption type, 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.