Taste Distillation

Taste Distillation

This standalone skill ships its implementation in scripts/; use taste-application for the subsequent generated or local-take edit. Keep each named genre in its own pack. Measurements from Flash Ethereal must not be silently reused for Fluid Sketch or 3D Cyber Glitch. A measured zero is valid data; distinguish it from an absent field.

Local dependencies are in scripts/requirements.txt. Separately authorized provider work also needs scripts/requirements-live.txt, credentials and explicit TASTE_FORGE_ALLOW_LIVE=1. --dry-run does not read credentials or submit jobs. Never infer that a workflow was saved from a local endpoint name; use the actual provider-side workflow or request evidence.

Turn reference videos into a style pack: a folder of measurements and assets that later stages consume deterministically.

When to Activate

• "capture the look of these clips" / "distill the vibe" / "make this repeatable"
• User has reference footage and wants a LUT, a grade, or matching pacing
• Building a library of looks partitioned by genre
• Any request where the answer would otherwise be "describe the style in a prompt"

The Core Finding

Prompting cannot deliver a grade. Measurement can.

Measured on real footage: three paid generations with escalating colour direction moved midtone a* from +1.9 → +2.8 → +0.3 against a +24.9 target, and contrast never left ~19 against a 34.7 target. Applying a measured pack to the same footage hit chroma MAE 1.88 and contrast 33.7 in one deterministic pass, for free.

So the split is: the model supplies content, motion and lighting structure; the pack supplies the look. Colour words in a generation prompt are worse than useless — they cost money and push the render away from the neutral base the LUT wants. Say so explicitly in the prompt: "Colour: none. Render neutral. Grading is applied afterwards."

What a Pack Contains

stylepacks/<genre>/
  grade.json      measured colour statistics (see below)
  cadence.json    every detected shot boundary + the derived distribution
  look.cube       33^3 LUT, drag straight into Resolve as a node LUT
  spec.json       VLM description, grounded in the measurements
  grounding.txt   the measured facts fed to the VLM
  stills/         full-res frames from the longest shots (conditioning images)
  plates/         screen-blend overlay elements lifted onto black
  props/          minted GLB meshes
  pack.json       manifest

Running It

python mint.py --genre <name> --refs a.mov b.mov c.mov     # offline, no API key
python distill.py --genre <name>                            # one VLM call

mint.py is pure numeric analysis — no network, no key, deterministic, so a pack can be regenerated rather than backed up.

The Measurements That Matter

Chroma by luminance zone, not globally

Colour identity usually lives in one luminance band. A global a*/b* offset mathematically cannot represent split-toning. Measure chroma inside zones (L* edges [0,15,35,55,75,100]).

A real signature: violet at L*25 (a* +24.9, b* −17.5), near-neutral at both ends. Reporting only the darkest and lightest zones calls that "uniform cast" — always print the whole curve.

Median + MAD, never mean + std

Chroma in real reference sets is strongly right-skewed. On one measured reel the mean midtone chroma was 36.9 against a median of 17.5, so a mean-based LUT pushed colour ~3x harder than the material warranted.

Contrast is std(L*), not white minus black

The white−black range is ~100 on almost any real footage and discriminates nothing.

Background share is a first-class statistic

Record the share of pixels below L*10. No moment of the distribution can see it: a clip can hold the right mean, std and chroma while its blacks have been lifted into grey. This is exactly how a grade once scored MAE 1.88 / contrast 33.7 while the actual frame was a muddy purple mess.

Mask the interface before measuring

Screen-recorded references carry static furniture — letterbox bars, a status bar, a like icon, caption text. All of it lands in the statistics as if it were the look: black bars inflate shadow weight, a red heart skews a* toward magenta. Temporal variance separates them cleanly — the footage moves, the interface does not — so no hand-tuned crop is needed. On real material this keeps ~65% of pixels.

Cadence needs an adaptive threshold

The right content-detector threshold is material-dependent: a high-contrast action reference cuts hard enough for 30, a moody one hides its cuts under it. Sweep descending thresholds and take the highest one that still recovers ≥90% of the shots the most sensitive setting finds — that biases toward real cuts over noise. Reject thresholds implying an absurd cut rate (>100/min); continuous camera moves trip the detector every frame.

Run the whole sweep in one decode pass with a shared StatsManager. The naive version re-decodes per threshold, which on 60fps source is the difference between seconds and minutes.