gauntlet

Automated UI evaluation uses Playwright to explore a running web app, capture screenshots, and apply a 4-criteria rubric to generate a formal scorecard. This process splits evaluation and generation to ensure critique quality gates are met before generating a single, cohesive UI improvement.

An autonomous design-improvement loop is a GAN-inspired workflow that separates an evaluator and a generator. The evaluator critiques a running UI and produces a structured scorecard, and only after quality gates are met does the generator produce one coherent improvement per cycle with iteration logging and changelog updates.

Yes, Playwright-based exploration and screenshot capture are used directly against a running UI to perform automated testing and formal UI critique. The captured visual data feeds into a 4-criteria rubric to produce a structured scorecard for design reviews and QA cycles.

Generating a prioritized UI fix requires applying a formal scorecard from an evaluator to trigger a generator. The system applies safety checks and outputs a single, targeted improvement with iteration logging and changelog updates to maintain traceability during QA cycles.

No, the workflow enforces quality gates by evaluating the running UI and logging top issues before any code changes are generated. It produces one cohesive improvement per cycle, ensuring that structured scoring and safety checks are completed before applying a targeted fix.

Generating one coherent improvement per cycle ensures structured scoring and safety checks are applied to a single, targeted fix rather than scattered changes. This GAN-inspired refinement loop logs each iteration and updates the changelog to maintain high-signal feedback and traceability.