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What is signs-of-ai-design?

febbhav/signs-of-ai-design — explained in plain English

Analysis updated 2026-05-18

3Audience · generalComplexity · 1/5Setup · easy

In one sentence

A community field guide that catalogs visual patterns common in AI-generated design across websites, images, video, logos, and more. Each entry explains why AI tools produce the pattern and how to avoid jumping to conclusions from a single match.

Mindmap

mindmap
  root((repo))
    What it does
      Catalogs AI design tells
      Open community list
      Inspired by AI text guide
    How it works
      Organized by medium
      Reliability labels
      Status labels
    Use cases
      Spot AI-made visuals
      Learn AI design habits
      Contribute new patterns
    Audience
      Designers
      Curious readers
      Community contributors
    Scope
      Web and app interfaces
      Images video logos
      Slides and print
    Ethics
      No single sign proves AI
      Do not harass people
      Human detection is poor

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Learn the common visual tells that suggest an image, website, or logo was made by an AI tool.

USE CASE 2

Contribute a new AI design pattern you have noticed to the open community list.

USE CASE 3

Review the reliability and status labels before deciding whether a pattern still indicates AI involvement.

USE CASE 4

Use the guide as a reference when auditing design work for repetitive AI-generated habits.

What is it built with?

Markdown

How does it compare?

febbhav/signs-of-ai-design000madz000/payload-test-api-route-handler0marildo/imago
Stars333
LanguageTypeScriptPython
Setup difficultyeasyeasyeasy
Complexity1/52/52/5
Audiencegeneraldevelopergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
No license information is provided in the repository, so default copyright terms apply and reuse may be restricted.

So what is it?

This repository is a community field guide that catalogs the visual patterns typical of AI-generated design. It covers websites, app interfaces, images, video, logos, slide decks, social graphics, illustration, and print. The project takes inspiration from a Wikipedia page that documents the tells of machine-written prose, and applies that same approach to machine-made visuals. It is structured as an open list that anyone can contribute to and build upon. The guide is organized into sections by medium and design element, such as web interfaces, images, video, logos, and documents. Each entry explains what to look for, why AI tools produce that specific pattern, and the false positives where human designers might make the same choice. Entries also carry two labels. One label for reliability describes how much a single match tells you, ranging from strong to weak. Another label for status notes whether the tell still applies to current tools, since AI models update and patch their recurring visual habits over time. A core rule of the guide is that no single sign proves AI involvement. Almost every pattern listed was originally invented by human designers. The guide argues that AI tools amplified the frequency and uniformity of these patterns until they became recognizable fingerprints. One match is considered noise. A stack of many matches with no deviation is considered a signature. The text warns against using the list to harass people, noting that identifying AI involvement is not evidence of low effort or deception, and that human detection accuracy is currently poor. The content covers specific details like the prevalence of certain color gradients, the default use of specific typefaces, and recurring layout choices in generated web pages. It explains how defaults from popular coding tools saturated training data and became the standard look of generated sites. The repository also includes a section on signs that no longer work and a discussion of why models converge on similar outputs. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1
Read the signs-of-ai-design field guide and list the top five visual tells for AI-generated websites, including why each pattern appears and its reliability label.
Prompt 2
Pick three entries from signs-of-ai-design and explain what false positives a human designer might produce that look the same as the AI tell.
Prompt 3
Draft a new entry for signs-of-ai-design following its format: describe the pattern, why AI tools produce it, common false positives, a reliability label, and a status label.
Prompt 4
Summarize the ethical guidance from signs-of-ai-design about why one matching pattern is not enough and how to avoid misusing the guide.

Frequently asked questions

What is signs-of-ai-design?

A community field guide that catalogs visual patterns common in AI-generated design across websites, images, video, logos, and more. Each entry explains why AI tools produce the pattern and how to avoid jumping to conclusions from a single match.

What license does signs-of-ai-design use?

No license information is provided in the repository, so default copyright terms apply and reuse may be restricted.

How hard is signs-of-ai-design to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is signs-of-ai-design for?

Mainly general.

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