lookdev-auto
Automated visual tuning: a vision or video model rates rendered variants in a loop. Render several labeled variants into one artifact, ask the model to rate them and suggest better values, render the suggestions, ask it to pick the best, repeat until good — the model is the eye, you run the loop.
automationrender-looptuningvision-modelvisual-eval
When to Use
Use whenever "looks/feels right" is the success criterion and there's no cheap numeric metric — animation easing/timing, zoom/camera feel, color grade, layout/spacing, design params, render/encoder settings, prompt params. Use the automated counterpart to lookdev when there's no human to sit the loop.
_Source: connerkward/lookdev-auto-skill (MIT)._
Visual eval loop — let a vision/video model tune what only an eye can judge
When the target is "does this LOOK/FEEL right" (not a number you can minimize), a vision model (image) or video-understanding model (motion/timing) can be the judge in a tight optimize loop. Worked reference: the screenstudio-alternative skill (iteration.py) (tuned zoom-animation feel via fal-ai/video-understanding).
The loop
- Render N labeled variants into ONE artifact. Vary the parameter(s) across a
- One model call, structured output. Send the single artifact with an explicit
small spread. Annotate each variant's params ON the artifact (burn the label in: "A · 2.2Hz · ζ0.5"). Images → a labeled grid/contact sheet. Video/motion → a labeled sequence (label card or burned-in overlay before/over each clip) so the model can compare temporally.
rubric (define what "good" means — and what "too much"/"too little" look like). Ask for **per-variant
Subscribers only
The full skill, its 1 bundled files and every download is included with every paid Complete AI plan.
Details
| Source | connerkward/lookdev-auto-skill |
|---|---|
| License | MIT |
| Risk label | safe ("critical" means the skill may run commands or touch files — read before use) |
| Files | SKILL.md |
| Added | 2026-06-16 |
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