Building an automated verification harness for brush feel

We were taking one step forward and two steps back tuning the subjective feel of the brush. After repeatedly losing the "magic" of a good stroke to regression bugs, I realized we needed a methodical way to evaluate tweaks. I built an automated visual comparison suite that captures macro and micro snapshots of kanji character strokes across a speed ladder. By running side-by-side A/B baselines, we can finally prove whether a new physical tip lag or viscosity adjustment is actually an improvement or just a different flavor of wrong.