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Law Of Similarity

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Owl-Listener
law-of-similarity

Apply the Law of Similarity — shared colour, shape, or size signals that elements belong to one category. Use when signalling relationships across distance. For grouping by position, use `law-of-proximity`.

Overview

PublisherOwl-Listener
Repositorydesigner-skills
Skill namelaw-of-similarity
Stars
3.1K
Forks
422
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Owl-Listener on GitHub. Read the source before you install it.

Installation

Install the Law Of Similarity AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Owl-Listener/designer-skills/tree/main/ui-design/skills/law-of-similarity
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Owl-Listener/designer-skills.git /tmp/designer-skills
mkdir -p .claude/skills
cp -r /tmp/designer-skills/ui-design/skills/law-of-similarity .claude/skills/law-of-similarity
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Law Of Similarity in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Law Of Similarity on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Law Of Similarity is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Law of Similarity

You are an expert in Gestalt visual perception and systematic visual language design.

What You Do

You apply the Law of Similarity to use shared visual attributes — shape, color, size, and style — to signal that elements belong to the same category or group, and to maintain that coding consistently so the signal stays meaningful.

The Principle

Elements that share visual characteristics are perceived as related, even when they are not spatially adjacent. The mind groups by likeness automatically and without instruction.

Similarity can be carried through:

  • Color: same fill signals same category, role, or state
  • Shape: icons all the same style (outline vs. filled vs. rounded) read as a set
  • Size: elements of equal size read as peers; size difference signals hierarchy
  • Style: same illustration weight, same type treatment, same corner radius, same stroke width

Similarity vs. Proximity

These are the two most fundamental Gestalt grouping principles. They interact and can conflict:

SituationWhat happens
Elements close together, same colorBoth reinforce — strongest grouping signal
Elements far apart, same colorSimilarity groups them despite the distance
Elements close together, different colorsProximity and similarity compete; the color pulls them into different sub-groups
Elements close together, different stylesProximity groups the set; style difference creates sub-groups within it

When they conflict, similarity can override proximity: a red element embedded in a group of blue elements reads as distinct even if it is spatially adjacent. Use this deliberately to signal category boundaries.

Design Applications

Interactive state signaling

All interactive elements should share a visual property (color, underline treatment, cursor affordance) that non-interactive elements do not. This tells users what is actionable without requiring explicit instruction — the similarity set defines the interactive category.

Category and role coding

  • Navigation items as a set: consistent type treatment across all items
  • Destructive actions: a distinctive color used only within that category — similarity within the set signals "these all carry the same risk"
  • Status indicators: consistent color-to-meaning mapping (green = success, amber = warning, red = error) applied uniformly

When any element deviates from an established similarity set without purpose, users read the deviation as meaningful — as if the deviant element belongs to a different category.

Design systems and component coherence

Similarity is the mechanism that makes a design system feel like one thing rather than a collection of unrelated components:

  • Same button shape across all button variants
  • Same input height and border treatment across all form elements
  • Same icon stroke weight and style across all icons

Unintended similarity breaks — two buttons with slightly different corner radii that are supposed to be the same type — read as categorical differences. Treat them as bugs.

Data visualisation

  • Same color = same data series across all charts in a report
  • Same mark shape = same variable across chart types
  • Grouping by similarity (color, shape) before spatial proximity is standard in multi-series visualisations

Common Mistakes

  • Breaking similarity unintentionally: slight visual inconsistencies in what should be a uniform set signal a difference the designer did not intend
  • Overusing a single attribute: coding too many distinct categories with the same color makes the attribute meaningless as a signal
  • Relying on color similarity alone: colorblind users cannot distinguish groups encoded only through hue — always use redundant coding

Best Practices

  • Define a similarity vocabulary in design tokens: which visual attributes encode which relationship types
  • Treat unintended visual differences as bugs — if two elements should read as the same type, they must look identical
  • Use redundant coding (shape + color, not color alone) for critical category signals so the information survives colorblind viewing and monochrome rendering
  • Test similarity groupings without color: do elements still read as related from shape and size alone?
  • Review dense layouts for unintended sub-groupings created by similarity interacting with proximity

Frequently asked questions

What does the Law Of Similarity AI skill do?

Apply the Law of Similarity — shared colour, shape, or size signals that elements belong to one category. Use when signalling relationships across distance. For grouping by position, use `law-of-proximity`.

Why use Law Of Similarity on TypingMind?

Because you install it once and use it with any model. Law Of Similarity is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Law Of Similarity in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Owl-Listener/designer-skills/tree/main/ui-design/skills/law-of-similarity. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Law Of Similarity?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Law Of Similarity?

As many as you like. As long as a model supports skills, you can use Law Of Similarity with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Law Of Similarity AI skill free?

Yes. It is published on GitHub by Owl-Listener under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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