Brand Gut Checker: AI-Powered Design Review in Figma

This started as a simple idea: what if you could get a quick gut check on whether a design feels on-brand without pulling someone into a review meeting? I built a Figma plugin that lets you select any frame, pick an LLM vision model (Claude, GPT-4, and others via OpenRouter), and get a scored evaluation against your stored brand guidelines. It breaks things down across dimensions — color usage, typography, layout, photography, mood — and gives you explanations for each score. You can also use the plugin to extract guidelines from existing frames or generate them from a text description, and everything gets stored in a dedicated Figma page so the whole team has access.

The fascinating discovery

Here’s what I didn’t expect: different models give wildly different scores for the exact same frame. One model scored a design at 25%, another gave it 85%. Same frame, same guidelines, completely different interpretations. That was a genuine “huh” moment. It reveals something important about how these vision models process visual information — they’re not just reading pixels, they’re interpreting intent and context, and they each have very different biases about what constitutes “good” adherence to a guideline. It’s a reminder that AI evaluation is still a complement to human judgment, not a replacement for it.

How it works under the hood

The plugin captures the selected frame as an image, sends it along with the stored guidelines to whichever model you’ve picked through the OpenRouter API, and parses the structured response back into the scoring UI. OpenRouter is the key piece here because it gives you multi-model access through a single API — so instead of managing separate API keys and integrations for every provider, you get one endpoint that can route to Claude, GPT-4, Gemini, and others. That’s what makes the model comparison possible without the plugin becoming an engineering nightmare to maintain.