| Summary | Automatically rates studios in Stash based on how you’ve rated their scenes and images. | |
| Repository | https://codeberg.org/surging9143/studioAutoRate | |
| Source URL | https://surging9143.codeberg.page/index.yml | |
| Install | How to install a plugin? |
How it works
Ratings use a Bayesian average: new studios start near your library’s mean and converge toward their true average as you rate more of their content. This prevents a single scene from inflating a studio you’ve barely seen.
Optional boosts add points on top of that average. Each boost has a multiplier you set (default 0 = off). Most use a log scale — the bonus grows with engagement but tapers off, so the difference between 1 and 10 plays matters more than between 100 and 110. The favorite boost is a flat addition. The tag boost accumulates once per favorite tag across all scenes and images, so studios whose content matches several of your favorited tags benefit more than those who only match one.
Configure multipliers under Settings → Plugins → Studio Auto Rater. Start small (1–2) and adjust to taste.
Usage
Automatic — runs whenever you update a scene, image, or studio.
Manual — Settings → Plugins → Studio Auto Rater → Rate All Studios. Use this after changing o-counts, which don’t trigger the hook.
Requirements
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Python 3
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stashapi (included in the official Stash Docker image)
