inspiration-analyzer
Analyze websites for design inspiration, extracting colors, typography, layouts, and patterns. Use when you have specific URLs to analyze for a design project.
Best use case
inspiration-analyzer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyze websites for design inspiration, extracting colors, typography, layouts, and patterns. Use when you have specific URLs to analyze for a design project.
Teams using inspiration-analyzer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/inspiration-analyzer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How inspiration-analyzer Compares
| Feature / Agent | inspiration-analyzer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyze websites for design inspiration, extracting colors, typography, layouts, and patterns. Use when you have specific URLs to analyze for a design project.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Coding
Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
ChatGPT vs Claude for Agent Skills
Compare ChatGPT and Claude for AI agent skills across coding, writing, research, and reusable workflow execution.
SKILL.md Source
# Inspiration Analyzer
Analyze websites to extract design inspiration including colors, typography, layouts, and UI patterns.
## Purpose
When a user provides inspiration URLs, this skill:
- Visits each site using browser tools
- Takes screenshots for visual analysis
- Extracts specific design elements
- Creates structured inspiration report
- Identifies replicable patterns
## Workflow
### Step 1: Get Browser Context
```javascript
// Get or create browser tab
tabs_context_mcp({ createIfEmpty: true })
tabs_create_mcp()
```
### Step 2: Navigate to URL
```javascript
navigate({ url: "https://example.com", tabId: tabId })
```
### Step 3: Capture Screenshots
Take multiple screenshots to capture the full experience:
1. **Hero/Above-fold**: Initial viewport
2. **Scrolled sections**: Scroll and capture
3. **Interactive states**: Hover on navigation, buttons
4. **Mobile view**: Resize to mobile width
```javascript
// Full page screenshot
computer({ action: "screenshot", tabId: tabId })
// Scroll and capture more
computer({ action: "scroll", scroll_direction: "down", tabId: tabId })
computer({ action: "screenshot", tabId: tabId })
// Mobile view
resize_window({ width: 375, height: 812, tabId: tabId })
computer({ action: "screenshot", tabId: tabId })
```
### Step 4: Analyze Elements
From screenshots and page content, extract:
#### Colors
- **Primary color**: Main brand color
- **Secondary colors**: Supporting palette
- **Background color**: Page and section backgrounds
- **Text colors**: Headings and body text
- **Accent colors**: CTAs, links, highlights
Note hex codes where visible.
#### Typography
- **Heading font**: Name if identifiable, or describe style
- **Body font**: Name or describe
- **Font weights**: Light, regular, bold usage
- **Size scale**: Relative sizes of elements
- **Line height**: Tight or generous
- **Letter spacing**: Tracking patterns
#### Layout
- **Grid system**: Column structure
- **White space**: Spacing philosophy
- **Section structure**: Full-width, contained, alternating
- **Navigation style**: Fixed, hidden, sidebar
- **Footer structure**: Minimal or comprehensive
#### UI Patterns
- **Buttons**: Shape, size, states
- **Cards**: Borders, shadows, corners
- **Icons**: Style (outlined, filled, custom)
- **Images**: Treatment, aspect ratios
- **Animations**: Motion patterns observed
### Step 5: Generate Report
Create a structured analysis:
```markdown
## Website Analysis: [URL]
### Screenshots
[Describe key screenshots taken]
### Color Palette
| Role | Hex | Usage |
|------|-----|-------|
| Primary | #xxx | [Where used] |
| Secondary | #xxx | [Where used] |
| Background | #xxx | [Where used] |
| Text | #xxx | [Where used] |
| Accent | #xxx | [Where used] |
### Typography
- **Headlines**: [Font name/description] - [weight]
- **Body**: [Font name/description] - [weight]
- **Scale**: [Size relationships]
- **Line height**: [Observation]
### Layout Patterns
- Grid: [Description]
- Spacing: [Description]
- Sections: [Description]
### UI Elements
- **Buttons**: [Description]
- **Cards**: [Description]
- **Navigation**: [Description]
- **Footer**: [Description]
### Key Takeaways
1. [What makes this design distinctive]
2. [Pattern worth replicating]
3. [Specific technique to use]
### What to Avoid
- [Any patterns from this site that are overused]
- [Elements that wouldn't translate well]
```
## Multiple Sites
When analyzing multiple URLs:
1. Analyze each separately
2. Create individual reports
3. Summarize common themes
4. Note contrasting approaches
5. Recommend which elements to combine
## Fallback Mode
If browser tools are unavailable:
1. Inform user that live analysis requires browser access
2. Ask user to:
- Share screenshots of the sites
- Describe what they like about each
- Paste any visible color codes
- Note font names if visible
3. Work with provided information to create analysis
## Best Practices
### For Accurate Color Extraction
- Look for color variables in page inspection
- Check buttons for primary brand color
- Note background color on different sections
- Capture hover states for accent colors
### For Typography Identification
- Look for Google Fonts link in source
- Check font-family in computed styles
- Note relative sizes between h1, h2, body
- Observe tracking on headings vs body
### For Layout Analysis
- Resize viewport to see responsive behavior
- Note breakpoints where layout changes
- Count columns in grid layouts
- Measure (visually) spacing consistency
## Output
The analysis should provide:
1. Actionable color palette (hex codes)
2. Typography recommendations
3. Layout patterns to replicate
4. UI component inspiration
5. Clear direction for moodboard
See `references/extraction-techniques.md` for detailed extraction methods.Related Skills
meeting-insights-analyzer
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
soft-screening-startup
Activate for ANY startup evaluation, investment screening, or company assessment. Triggers include: "evaluate this startup", "screen this company", "should I invest in X", "is this a good investment", "what do you think about this company", "review this startup", "score this company", "rate this pitch", "assess this founder", "quick take on X", "is X worth investing in", "pass or decline on X", "what's your verdict on X", "first look at this company", "quick screen on X", "what's your take on this founder", "is this fundable", "would a VC invest in this". Also triggers when a user pastes a company description, funding ask, or founder background and asks for an opinion. Works on claude.ai and Claude Code. For hard-mode deterministic scoring with Python audit trail, use /venture-capital-intelligence:hard-screening-startup.
market-size
Run TAM/SAM/SOM market sizing with top-down and bottom-up methods, competitive landscape, and tech stack analysis. Triggered by: "/venture-capital-intelligence:market-size", "size this market", "what is the TAM for X", "market sizing analysis", "competitive landscape for X", "who are the competitors", "TAM SAM SOM for X", "market opportunity analysis", "how big is this market", "is this market big enough", "what's the addressable market", "total addressable market for X", "how large is the opportunity", "market research for X", "how saturated is this market", "market size estimate", "go-to-market sizing", "what is the serviceable market". Claude Code only. Requires Python 3.x. Uses web search for market data.
hard-screening-startup
Deterministic Python-scored startup screening with full audit trail. Use when you need a reproducible, weighted-score verdict on a startup — not just a qualitative opinion. Triggered by: "/venture-capital-intelligence:hard-screening-startup", "hard screen this startup", "run a hard screen on X", "score this startup with Python", "give me an auditable screen", "run a scored evaluation on X", "give me a weighted score for this startup", "screen with numbers", "objective startup score", "reproducible screen", "investment scorecard for X", "score this company out of 100", "run the full screen on X". Claude Code only. Requires Python 3.x. For conversational soft-mode screening, use /venture-capital-intelligence:soft-screening-startup.
fund-operations
Compute fund KPIs (TVPI, DPI, IRR, MOIC), model carried interest and management fees, and generate LP quarterly update narratives. Triggered by: "/venture-capital-intelligence:fund-operations", "calculate fund KPIs", "what is my fund TVPI", "IRR calculation", "compute MOIC", "LP report", "quarterly update draft", "carried interest calculation", "management fee calculation", "fund performance report", "write my LP update", "how is my fund performing", "what is my DPI", "fund returns analysis", "model my carry", "how much carry do I earn", "portfolio performance summary", "generate investor update". Claude Code only. Requires Python 3.x.
financial-model
Run deterministic financial models for startup valuation and SaaS health analysis. Triggered by: "/venture-capital-intelligence:financial-model", "run a financial model on X", "DCF this company", "model the financials", "calculate runway", "what is the valuation", "SaaS metrics model", "LTV CAC analysis", "unit economics", "burn rate analysis", "comparable valuation", "how long is my runway", "what's my burn multiple", "revenue projection for X", "model the ARR growth", "what is the pre-money valuation", "comps analysis", "NRR and churn model", "how healthy are these SaaS metrics". Claude Code only. Requires Python 3.x. Accepts user-supplied numbers or searches for publicly available data.
explain-equity-terms
Activate for ANY equity, legal, or term sheet question related to startup investing or fundraising. Triggers include: "what is a SAFE", "explain this term sheet", "what does pro-rata mean", "what is liquidation preference", "explain anti-dilution", "ISO vs NSO", "what is a 83(b) election", "what is carried interest", "explain drag-along", "what is a valuation cap", "what does MFN mean", "explain convertible note vs SAFE", "what is a down round", "explain vesting cliff", "what does fully diluted mean", "term sheet question", "equity question", "what does this clause mean". Also triggers when a user pastes legal text from a term sheet, SAFE, or subscription agreement and asks what it means. Works on claude.ai and Claude Code.
deal-sourcing-signals
Scan a company or sector for deal-sourcing signals across 6 dimensions. Triggered by: "/venture-capital-intelligence:deal-sourcing-signals", "scan signals for X", "what signals is X showing", "deal sourcing scan", "hiring signals for X", "is X raising soon", "monitor this company", "company signal scan", "sourcing brief for X", "what is X up to", "is X growing", "track this company", "deal signal report for X", "is this company fundraising", "what are the momentum signals for X", "find signals on X", "is X worth tracking". Claude Code only. Requires Python 3.x. Uses web search for live signal data.
cap-table-waterfall
Model cap table dilution, SAFE conversion, and exit waterfall across scenarios. Triggered by: "/venture-capital-intelligence:cap-table-waterfall", "model my cap table", "simulate dilution", "SAFE conversion math", "exit waterfall", "how much do I own after Series A", "liquidation waterfall", "cap table scenario", "what happens to equity at exit", "model the waterfall", "how much equity do I have left", "what is my ownership after funding", "run dilution scenarios", "model a new round", "what happens at acquisition", "cap table after SAFE conversion", "pari passu waterfall", "preference stack analysis". Claude Code only. Requires Python 3.x.
analyze-pitch-deck
Activate for ANY pitch deck analysis, feedback, or review request. Triggers include: "analyze this deck", "review my pitch deck", "critique my pitch", "feedback on my slides", "is my deck investor ready", "what's wrong with my pitch", "how would a VC react to this deck", "score my pitch deck", "rate my slides", "improve my deck", "what slides am I missing", "is this pitch compelling". Also triggers when a user pastes slide content, describes their deck structure, or shares a company narrative and asks for investor feedback. Works on claude.ai and Claude Code.
public-plugin-builder
Activate when the user wants to build a Claude plugin, create a Claude skill, make a Claude agent, structure a Claude Code plugin, says "build a plugin", "create a skill", "new claude skill", "new agent", "help me make a plugin", "plugin builder", "claude plugin helper", "how do I build a Claude skill", "I want to create a Claude plugin", "plugin building", or asks how to structure a Claude Code plugin or publish to the Claude marketplace. Works on both claude.ai (generates files as code blocks) and Claude Code (writes and pushes files).
server-components
This skill should be used when the user asks about "Server Components", "Client Components", "'use client' directive", "when to use server vs client", "RSC patterns", "component composition", "data fetching in components", or needs guidance on React Server Components architecture in Next.js.