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hyperframes/skills/hyperframes-captions/dynamic-techniques.md
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Vance IngallsandClaude Opus 4.6 3b5753c8a8 feat(captions): energy-based technique selection and mandatory quality checks
- Rewrite script-to-style mapping as energy detection table
- Add mandatory animation design requirements (karaoke baseline, technique cycling)
- Simplify dynamic-techniques.md to technique selection reference
- Add transcript quality check with automatic retry rules
- Add multilingual model guidance and decision tree

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-01 23:37:08 -07:00

5.7 KiB

Dynamic Caption Techniques

You are here because SKILL.md told you to read this file before writing animation code. Pick your technique combination from the table below based on the energy level you detected from the transcript, then implement using standard GSAP patterns.

Technique Selection by Energy

Energy level Highlight Exit Cycle pattern
High Karaoke with accent glow + scale pop Scatter or drop Alternate highlight styles every 2 groups
Medium-high Karaoke with color pop Scatter or collapse Alternate every 3 groups
Medium Karaoke (subtle, white only) Fade + slide Alternate every 3 groups
Medium-low Karaoke (minimal scale change) Fade Single style, vary ease per group
Low Karaoke (warm tones, slow transition) Collapse Alternate every 4 groups

All energy levels use karaoke highlight as the baseline. The difference is intensity — high energy gets accent color + glow + 15% scale pop on active words, low energy gets a gentle white shift with 3% scale.

Emphasis words always break the pattern. When a word is flagged as emphasis (emotional keyword, ALL CAPS, brand name), give it a stronger animation than surrounding words (larger scale, accent color, overshoot ease). This creates contrast.

Audio-Reactive Captions

No special wiring is needed. The group loop already iterates over every caption group to build entrance, karaoke, and exit tweens. At that point, read the audio data for each group's time range and use it to modulate the group's animation intensity with regular GSAP tweens.

// Load audio data inline (same pattern as TRANSCRIPT)
var AUDIO = JSON.parse(audioDataJson); // { fps, totalFrames, frames: [{ bands: [...] }] }

GROUPS.forEach(function (group, gi) {
  var groupEl = document.getElementById("cg-" + gi);
  if (!groupEl) return;

  // Read peak energy for this group's time range
  var startFrame = Math.floor(group.start * AUDIO.fps);
  var endFrame = Math.min(Math.floor(group.end * AUDIO.fps), AUDIO.totalFrames - 1);
  var peakBass = 0;
  var peakTreble = 0;
  for (var f = startFrame; f <= endFrame; f++) {
    var frame = AUDIO.frames[f];
    if (!frame) continue;
    peakBass = Math.max(peakBass, frame.bands[0] || 0, frame.bands[1] || 0);
    peakTreble = Math.max(peakTreble, frame.bands[6] || 0, frame.bands[7] || 0);
  }

  // Modulate entrance — louder groups enter bigger and glowier
  tl.to(
    groupEl,
    {
      scale: 1 + peakBass * 0.06,
      textShadow:
        "0 0 " + Math.round(peakTreble * 12) + "px rgba(255,255,255," + peakTreble * 0.4 + ")",
      duration: 0.3,
      ease: "power2.out",
    },
    group.start,
  );

  // Reset at exit so audio-driven values don't persist
  tl.set(groupEl, { scale: 1, textShadow: "none" }, group.end - 0.15);
});

This shapes the animation at build time, not playback time — no per-frame callbacks, no tl.call() loops, no async fetch timing issues. Loud groups come in with more weight and glow; quiet groups come in soft. The audio data modulates how much, the content determines what.

Keep audio reactivity subtle — 3-6% scale variation and soft glow. Heavy pulsing makes text unreadable.

To generate the audio data file:

python3 skills/gsap-effects/scripts/extract-audio-data.py audio.mp3 --fps 30 --bands 8 -o audio-data.json

Combining Techniques

Don't use the same highlight animation on every group — cycle through styles using the group index. Don't combine multiple competing animations on the same word at the same timestamp. Vary techniques across groups to match the content's pace changes.

Available Tools

These tools are available in the HyperFrames runtime. Use them when they solve a real problem — not every composition needs all of them.

Tool What it does Access When it's useful
pretext Pure-arithmetic text measurement without DOM reflow. 0.0002ms per call. window.__hyperframes.pretext.prepare(text, font) / .layout(prepared, maxWidth, lineHeight) Per-frame text reflow, shrinkwrap containers, computing layout before render
fitTextFontSize Finds the largest font size that fits text on one line. Built on pretext. window.__hyperframes.fitTextFontSize(text, { maxWidth, fontFamily, fontWeight }) Overflow prevention for long phrases, portrait mode, large base sizes
audio data Pre-extracted per-frame RMS energy and frequency bands. Extract with extract-audio-data.py, load inline or via fetch("audio-data.json") Audio-reactive visuals — modulate intensity based on the music
GSAP Animation timeline with tweens and callbacks. gsap.to(), gsap.set(), tl.to(), tl.set() All caption animation