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Design Research

Community
hamelsmu
design-research

Conduct comprehensive design research on any website or web application using a team of browser-automation agents. Use when asked to analyze, audit, or document a website's design system, UX patterns, layout, typography, colors, components, accessibility, responsive behavior, and technical implementation.

Overview

Publisherhamelsmu
Repositorydesign-research
Skill namedesign-research
Stars
78
Forks
6
Bundled files
Instructions only
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 hamelsmu on GitHub. Read the source before you install it.

Installation

Install the Design Research 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/hamelsmu/design-research/tree/main/skills/design-research
  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/hamelsmu/design-research.git /tmp/design-research
mkdir -p .claude/skills
cp -r /tmp/design-research/skills/design-research .claude/skills/design-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design Research 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 Design Research 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 Design Research 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.

Website Design Research

You are orchestrating a comprehensive design research audit of a website. You will create an agent team with parallel browser-automation agents to investigate every aspect of the site's design and implementation.

Input

The user provides a URL to research: $ARGUMENTS

If no URL was provided, ask the user for the target URL before proceeding.

Critical Requirements

  1. You MUST use agent teams (TeamCreate, TaskCreate, TaskUpdate, SendMessage, etc.) — NOT loose subagents via the Task tool
  2. Every teammate MUST use mcp__claude-in-chrome__* browser automation tools — never WebFetch, curl, or any other method
  3. You (the lead) MUST synthesize all findings into a single output file when all agents are done. The user specifies the output path; if they don't, default to notes/design-research.md. Do NOT just concatenate raw agent reports — read through all findings, resolve duplicates, ensure consistent formatting, fill in cross-references between sections, and produce a cohesive, well-structured document.

Browser Tool Startup Sequence (for every teammate)

Every agent must follow this sequence when starting:

  1. mcp__claude-in-chrome__tabs_context_mcp — get browser context
  2. mcp__claude-in-chrome__tabs_create_mcp — create a new tab
  3. mcp__claude-in-chrome__navigate — go to the target URL
  4. mcp__claude-in-chrome__computer (action=screenshot) — capture visual state
  5. mcp__claude-in-chrome__read_page — inspect DOM/accessibility tree
  6. mcp__claude-in-chrome__javascript_tool — extract computed styles, class names, data
  7. mcp__claude-in-chrome__find — locate specific elements by description
  8. mcp__claude-in-chrome__computer (action=scroll) — see content below the fold

Key tools by purpose

PurposeTool
Navigate to URLsmcp__claude-in-chrome__navigate
Take screenshotsmcp__claude-in-chrome__computer (action=screenshot)
Read DOM / accessibility treemcp__claude-in-chrome__read_page
Run JavaScript (computed styles, data extraction)mcp__claude-in-chrome__javascript_tool
Click elementsmcp__claude-in-chrome__computer (action=left_click)
Find elements by descriptionmcp__claude-in-chrome__find
Scroll the pagemcp__claude-in-chrome__computer (action=scroll)
Resize viewport (responsive testing)mcp__claude-in-chrome__resize_window
Read page text contentmcp__claude-in-chrome__get_page_text
Read console logsmcp__claude-in-chrome__read_console_messages
Read network requestsmcp__claude-in-chrome__read_network_requests

Research Areas (10 Tasks)

Task 1: Site Structure & Navigation

  • Map all top-level URLs and page types (home, product, content, settings, etc.)
  • Document the navigation hierarchy (breadcrumbs, sidebar, tabs, footer links)
  • Identify navigation redundancy patterns (how many ways to get to the same content)
  • Note URL patterns and routing conventions
  • Identify navigation gaps (missing back-links, dead ends, no search, etc.)

Task 2: Page Layout & Chrome (per page type)

  • For each distinct page type, document the shared "chrome" (header, sidebar, footer)
  • Measure column layout (widths, sticky behavior, responsive breakpoints)
  • Document the top bar elements (icons, toggles, user menu)
  • Note which chrome elements appear/disappear per page type (build a Page Chrome Matrix)
  • Record CSS classes and measurements for key layout containers

Task 3: Design System — Colors & Typography

  • Extract exact color values (RGB/hex) for backgrounds, text, links, borders, accents
  • Document the font stack (families, sizes, weights, line-heights per element)
  • Capture syntax highlighting color scheme if code is present
  • Note the color hierarchy and how it creates depth/layering
  • Document the button system (variants, sizes, states)
  • Identify whether CSS custom properties or utility classes are used

Task 4: Interactive Components Inventory

  • Catalog every interactive component: forms, modals, accordions, toggles, collapsibles, carousels, players, search, etc.
  • Document each component's states (collapsed/expanded, active/inactive, loading, error, disabled)
  • Note toolbar buttons and their functions
  • Identify the underlying libraries (if visible in DOM/network)

Task 5: Content Type Templates (per type)

  • For each distinct content/page type, document:
    • The exact content flow (e.g., H1 → hero → body → sidebar → CTA → footer)
    • Unique elements per type
    • Variants within the type
  • Build a Content Template Matrix showing which features appear on which page types

Task 6: UX Patterns & Micro-interactions

  • Progressive disclosure patterns (what's hidden by default, how it reveals)
  • State persistence (localStorage, cookies, URL params, session tracking)
  • Gamification elements (progress bars, badges, streaks, points, rewards)
  • Callout/info box styles and when each is used (info vs warning vs success vs error)
  • Hover effects, transitions, and animations
  • Loading states and skeleton screens

Task 7: Visual Design & Personality (qualitative)

  • Illustrations, icons, and visual metaphors
  • Whimsical or distinctive details (dividers, badges, mascots, copy tone)
  • Typography warmth and font pairing analysis
  • Overall emotional tone and brand personality
  • Comparison to common design paradigms (minimal, editorial, playful, corporate, etc.)
  • What makes this design memorable or distinctive

Task 8: Mobile & Responsive Behavior

  • Resize to mobile breakpoint and document what changes
  • Sidebar → drawer conversions
  • Touch targets and hamburger menu behavior
  • Features that are desktop-only
  • Critical mobile issues (missing navigation, undersized targets, viewport bugs)
  • Document all breakpoints used

Task 9: Technical Implementation

  • Identify the framework (React, Vue, Next.js, Nuxt, Svelte, etc.)
  • Identify CSS approach (Tailwind, styled-components, CSS modules, vanilla, etc.)
  • Key component/class naming conventions visible in DOM
  • Libraries and services (video hosting, analytics, auth providers, CDNs, etc.)
  • API endpoints and data fetching patterns visible in network tab
  • SEO implementation (meta tags, OG tags, structured data, canonical URLs)

Task 10: Accessibility & Semantics

  • Heading hierarchy (proper H1 → H2 → H3 nesting)
  • ARIA attributes on interactive elements
  • Semantic HTML usage (main, nav, header, footer, aside, section, article)
  • Keyboard navigability of key components
  • Skip-to-content links
  • Color contrast adequacy (check muted text on light backgrounds especially)
  • Screen reader friendliness (labeled inputs, alt text, etc.)
  • Assign an overall accessibility grade (A through F)

Execution Strategy

Dependencies

TaskDependenciesNotes
1. Site StructureNoneMap the site first
2. Page LayoutsTask 1Needs page types identified
3. Design SystemNoneCan run immediately
4. ComponentsTask 1Needs site map to find all component types
5. Content TemplatesTask 1Needs page types identified
6. UX PatternsTask 1Needs site map for thorough coverage
7. Visual DesignNoneCan run immediately
8. Mobile/ResponsiveTask 2Needs layout baseline for comparison
9. Technical Impl.NoneCan run immediately
10. AccessibilityNoneCan run immediately

Three-Pass Execution

First pass (5 agents, parallel, no dependencies): Tasks 1, 3, 7, 9, 10

Second pass (4 agents, parallel, after Task 1 completes): Tasks 2, 4, 5, 6

Third pass (1 agent, after Task 2 completes): Task 8

Team Orchestration Procedure

Follow these steps exactly:

  1. Create the team: TeamCreate with name like design-research-{site}
  2. Create all 10 tasks: Use TaskCreate for each research area
  3. Set dependencies: Use TaskUpdate with addBlockedBy to wire up the dependency chain
  4. Spawn first-pass agents (5 agents for Tasks 1, 3, 7, 9, 10):
    • Each agent prompt must include:
      • The target URL
      • The specific research task description (copy from above)
      • The browser tool startup sequence
      • Instruction to report findings back via SendMessage
    • Use team_name parameter on the Task tool to attach agents to the team
  5. As agents complete:
    • Mark their tasks as completed via TaskUpdate
    • Send shutdown requests via SendMessage
    • Approve shutdown responses
  6. When Task 1 completes: spawn second-pass agents (Tasks 2, 4, 5, 6), passing the site map from Task 1's findings
  7. When Task 2 completes: spawn third-pass agent (Task 8), passing the layout findings
  8. After all agents complete — SYNTHESIZE: This is your most important job as lead. Read through ALL agent reports and synthesize them into a single cohesive markdown document at the output path the user specified (default: notes/design-research.md). Do not just paste reports together — resolve duplicates, ensure consistent formatting, add cross-references between sections (e.g., link color findings to accessibility contrast issues), and produce a polished, well-organized reference document.
  9. Clean up: TeamDelete to remove team resources

Output Format

Compile all findings into a single markdown file with this structure:

markdown
# {Site Name} — Design & UX Research Report

> **URL**: {target URL}
> **Date**: {today's date}
> **Summary**: One-line description of the site's design approach

---

## Table of Contents
[Auto-generated from sections below]

## 1. Site Structure & Navigation
[Findings from Task 1]

## 2. Page Layouts & Chrome
[Findings from Task 2]

## 3. Design System — Colors & Typography
[Findings from Task 3 — include color tables with hex values and Tailwind equivalents]

## 4. Interactive Components
[Findings from Task 4]

## 5. Content Type Templates
[Findings from Task 5]

## 6. UX Patterns & Micro-interactions
[Findings from Task 6]

## 7. Visual Design & Personality
[Findings from Task 7]

## 8. Mobile & Responsive Behavior
[Findings from Task 8]

## 9. Technical Implementation
[Findings from Task 9 — include architecture diagram]

## 10. Accessibility & Semantics
[Findings from Task 10 — include grade and top recommendations]

Use tables, code blocks, and structured formatting throughout. Include exact CSS values, class names, hex colors, and measurements — not vague descriptions.

Frequently asked questions

What does the Design Research AI skill do?

Conduct comprehensive design research on any website or web application using a team of browser-automation agents. Use when asked to analyze, audit, or document a website's design system, UX patterns, layout, typography, colors, components, accessibility, responsive behavior, and technical implementation.

Why use Design Research on TypingMind?

Because you install it once and use it with any model. Design Research 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 Design Research in TypingMind?

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

Which AI models can use Design Research?

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 Design Research?

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

Is the Design Research AI skill free?

It is published on GitHub by hamelsmu. Check the repository for licensing terms. 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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