index.scroll
Changed around line 1
+ buildHtml
+ baseUrl https://badleaders.scroll.pub
+ metaTags
+ editButton /edit.html
+ title Bad Leaders PCA
+ style.css
+ header
+ class hero
+ nav
+ div Bad Leaders
+ class logo
+ div
+ class nav-links
+ a About
+ href #about
+ a How It Works
+ href #how-it-works
+ a GitHub
+ class cta-button
+ href https://github.com/yourusername/badleaders
+ div
+ class hero-content
+ h1 Bad Leaders PCA
+ p Visualizing the worst leaders in history
+ p Enter a leader's traits below to find their historical match
+ main
+ section
+ id pca-plot
+ class pca-plot
+ div
+ class plot-container
+ canvas
+ id leaderPlot
+ section
+ id leader-input
+ class leader-input
+ h2 Find Your Match
+ div
+ class input-container
+ input
+ type text
+ id leaderTraits
+ placeholder Describe a leader (e.g. authoritarian, corrupt, charismatic...)
+ button
+ id findMatch
+ Find Match
+ div
+ id matchResult
+ class match-result
+ section
+ id about
+ class about
+ h2 About This Project
+ p This PCA plot visualizes historical leaders based on traits like authoritarianism, corruption, and charisma. The data is synthesized for educational purposes.
+ section
+ id how-it-works
+ class how-it-works
+ h2 How It Works
+ p The plot uses Principal Component Analysis to reduce leader traits into 2D space. When you describe a leader, it finds the closest match in the dataset.
+ footer
+ div
+ class footer-content
+ div
+ class footer-links
+ a Data Source
+ href #
+ a Methodology
+ href #
+ a GitHub
+ href https://github.com/yourusername/badleaders
+ p Educational project by [Your Name]
+ script.js
prompt.json
Changed around line 1
+ {
+ "id": "3bdd924a-74ba-4aeb-bd71-8a0343571dad",
+ "object": "chat.completion",
+ "created": 1738201472,
+ "model": "deepseek-chat",
+ "choices": [
+ {
+ "index": 0,
+ "message": {
+ "role": "assistant",
+ "content": "---domain---\nbadleaders.scroll.pub\n---index.scroll---\nbuildHtml\nbaseUrl https://badleaders.scroll.pub\nmetaTags\neditButton /edit.html\ntitle Bad Leaders PCA\nstyle.css\nheader\n class hero\n nav\n div Bad Leaders\n class logo\n div\n class nav-links\n a About\n href #about\n a How It Works\n href #how-it-works\n a GitHub\n class cta-button\n href https://github.com/yourusername/badleaders\n div\n class hero-content\n h1 Bad Leaders PCA\n p Visualizing the worst leaders in history\n p Enter a leader's traits below to find their historical match\nmain\n section\n id pca-plot\n class pca-plot\n div\n class plot-container\n canvas\n id leaderPlot\n section\n id leader-input\n class leader-input\n h2 Find Your Match\n div\n class input-container\n input\n type text\n id leaderTraits\n placeholder Describe a leader (e.g. authoritarian, corrupt, charismatic...)\n button\n id findMatch\n Find Match\n div\n id matchResult\n class match-result\nsection\n id about\n class about\n h2 About This Project\n p This PCA plot visualizes historical leaders based on traits like authoritarianism, corruption, and charisma. The data is synthesized for educational purposes.\nsection\n id how-it-works\n class how-it-works\n h2 How It Works\n p The plot uses Principal Component Analysis to reduce leader traits into 2D space. When you describe a leader, it finds the closest match in the dataset.\nfooter\n div\n class footer-content\n div\n class footer-links\n a Data Source\n href #\n a Methodology\n href #\n a GitHub\n href https://github.com/yourusername/badleaders\n p Educational project by [Your Name]\nscript.js\n---style.css---\n:root {\n --gradient-primary: linear-gradient(135deg, #ff416c, #ff4b2b);\n --gradient-secondary: linear-gradient(135deg, #4776e6, #8e54e9);\n --text-primary: #ffffff;\n --text-secondary: #e0e0e0;\n --background-dark: #1a1a1a;\n --background-light: #2d2d2d;\n --accent-color: #ff4b2b;\n}\n\nbody {\n background: var(--background-dark);\n color: var(--text-primary);\n font-family: 'Segoe UI', sans-serif;\n margin: 0;\n padding: 0;\n line-height: 1.6;\n}\n\n.hero {\n background: var(--gradient-primary);\n padding: 4rem 2rem;\n text-align: center;\n}\n\n.logo {\n font-size: 2rem;\n font-weight: bold;\n margin-bottom: 1rem;\n}\n\n.hero-content h1 {\n font-size: 3rem;\n margin-bottom: 1rem;\n}\n\n.pca-plot {\n padding: 2rem;\n background: var(--background-light);\n}\n\n.plot-container {\n width: 90%;\n max-width: 800px;\n margin: 0 auto;\n height: 500px;\n}\n\ncanvas {\n width: 100%;\n height: 100%;\n background: var(--background-dark);\n border-radius: 10px;\n}\n\n.leader-input {\n padding: 2rem;\n text-align: center;\n}\n\n.input-container {\n max-width: 600px;\n margin: 0 auto;\n}\n\ninput[type=\"text\"] {\n width: 100%;\n padding: 1rem;\n border: none;\n border-radius: 5px;\n margin-bottom: 1rem;\n background: var(--background-light);\n color: var(--text-primary);\n}\n\nbutton {\n background: var(--accent-color);\n color: white;\n padding: 1rem 2rem;\n border: none;\n border-radius: 5px;\n cursor: pointer;\n transition: transform 0.2s;\n}\n\nbutton:hover {\n transform: scale(1.05);\n}\n\n.match-result {\n margin-top: 2rem;\n padding: 1rem;\n background: var(--background-light);\n border-radius: 5px;\n}\n\n@media (max-width: 768px) {\n .hero-content h1 {\n font-size: 2rem;\n }\n \n .plot-container {\n height: 300px;\n }\n}\n---script.js---\n// Generate random PCA-like data\nfunction generateRandomLeaders(num) {\n const leaders = [];\n for (let i = 0; i < num; i++) {\n leaders.push({\n x: Math.random() * 2 - 1,\n y: Math.random() * 2 - 1,\n name: `Leader ${i + 1}`,\n traits: {\n authoritarianism: Math.random(),\n corruption: Math.random(),\n charisma: Math.random(),\n longevity: Math.random()\n }\n });\n }\n return leaders;\n}\n\n// Initialize plot\nfunction initPlot() {\n const canvas = document.getElementById('leaderPlot');\n const ctx = canvas.getContext('2d');\n const leaders = generateRandomLeaders(200);\n \n // Draw points\n leaders.forEach(leader => {\n const x = (leader.x + 1) * canvas.width / 2;\n const y = (leader.y + 1) * canvas.height / 2;\n \n ctx.beginPath();\n ctx.arc(x, y, 3, 0, 2 * Math.PI);\n ctx.fillStyle = '#ff4b2b';\n ctx.fill();\n });\n\n // Find match functionality\n document.getElementById('findMatch').addEventListener('click', () => {\n const input = document.getElementById('leaderTraits').value.toLowerCase();\n const match = findClosestMatch(input, leaders);\n document.getElementById('matchResult').textContent = `Closest match: ${match.name}`;\n });\n}\n\n// Simple matching algorithm\nfunction findClosestMatch(input, leaders) {\n // Convert input to trait scores (very basic implementation)\n const inputTraits = {\n authoritarianism: input.includes('authoritarian') ? 1 : 0,\n corruption: input.includes('corrupt') ? 1 : 0,\n charisma: input.includes('charismatic') ? 1 : 0,\n longevity: input.includes('long') ? 1 : 0\n };\n\n // Find closest match\n let closest = leaders[0];\n let minDistance = Infinity;\n \n leaders.forEach(leader => {\n const distance = Math.sqrt(\n Math.pow(leader.traits.authoritarianism - inputTraits.authoritarianism, 2) +\n Math.pow(leader.traits.corruption - inputTraits.corruption, 2) +\n Math.pow(leader.traits.charisma - inputTraits.charisma, 2) +\n Math.pow(leader.traits.longevity - inputTraits.longevity, 2)\n );\n \n if (distance < minDistance) {\n minDistance = distance;\n closest = leader;\n }\n });\n\n return closest;\n}\n\n// Initialize when DOM is loaded\ndocument.addEventListener('DOMContentLoaded', initPlot);\n---end---"
+ },
+ "logprobs": null,
+ "finish_reason": "stop"
+ }
+ ],
+ "usage": {
+ "prompt_tokens": 797,
+ "completion_tokens": 1603,
+ "total_tokens": 2400,
+ "prompt_tokens_details": {
+ "cached_tokens": 0
+ },
+ "prompt_cache_hit_tokens": 0,
+ "prompt_cache_miss_tokens": 797
+ },
+ "system_fingerprint": "fp_3a5770e1b4"
+ }
readme.scroll
Changed around line 1
+ # badleaders.scroll.pub
+
+ Prompt: website
+ Agent: deepseek
+ Model: deepseek-chat
+
+ ## User prompt
+ Build a website which shows a PCA plot of all bad historical world leaders in history. It should show about 200 randomly drawn dots. And then you should be able to describe a world leader and it will show you which leader from history is most like the leader you are running against. Show there should be one input. As much as possible above the fold. Make it look visually appealing. Cool gradients etc.
+
+ ## System prompt
+ You are an expert web developer. Create a website based on this request: "Build a website which shows a PCA plot of all bad historical world leaders in history. It should show about 200 randomly drawn dots. And then you should be able to describe a world leader and it will show you which leader from history is most like the leader you are running against. Show there should be one input. As much as possible above the fold. Make it look visually appealing. Cool gradients etc."
+
+ Requirements:
+ - Use only Scroll, CSS, and JavaScript (NO frameworks, NO external dependencies)
+ - Create clean, semantic HTML5
+ - Make it mobile-responsive
+ - Follow modern best practices and accessibility guidelines
+ - Keep it simple but professional
+ - Use only relative links and no external resources
+ - Do not put a copyright symbol or all rights reserved in the footer.
+ - Make it beautiful. Dazzling. Advanced used of CSS.
+
+ As a refresher, for doing the html body, Scroll is a whitespace based language that uses a single indented space to mark a line (aka particle) as a subparticle of a parent line.
+
+ For example:
+
+ header
+ class hero
+ nav
+ div Scroll
+ class logo
+ div
+ class nav-links
+ a Features
+ href #features
+ a Examples
+ href #examples
+ a Edit
+ href edit.html
+ a GitHub
+ class cta-button
+ href https://github.com/breck7/scroll
+ div
+ class hero-content
+ h1 Write Better with Scroll
+ p The extendible markup language that makes source beautiful and compiles to anything
+ a Get Started
+ class primary-button
+ href https://hub.scroll.pub/
+ main
+ section
+ id features
+ class features
+ h2 Why Scroll?
+ div
+ class feature-grid
+ div
+ class feature-card
+ div ⚡
+ class feature-icon
+ h3 Simple Syntax
+ p Like Markdown, but more powerful. No parentheses needed.
+ div
+ class feature-card
+ div 🧩
+ class feature-icon
+ h3 Extendible
+ p Build your own custom parsers.
+ div
+ class feature-card
+ div 🎨
+ class feature-icon
+ h3 Beautiful Output
+ p Create stunning documents with minimal effort.
+ div
+ class feature-card
+ div 🚀
+ class feature-icon
+ h3 Fast & Light
+ p Built on the efficient PPS Stack.
+ section
+ id examples
+ class code-demo
+ h2 See It In Action
+ div
+ class code-container
+ pre
+ class code-example
+ div
+ class code-output
+ footer
+ div
+ class footer-content
+ div
+ class footer-links
+ a Documentation
+ href https://scroll.pub/tutorial.html
+ a Community
+ href https://www.reddit.com/r/WorldWideScroll/
+ a Blog
+ href https://scroll.pub/blog
+ p Started by Breck Yunits. Evolved by a community.
+ https://twitter.com/breckyunits Breck Yunits
+ https://github.com/breck7/scroll/graphs/contributors community
+
+
+ First suggest a short, memorable domain name ending in scroll.pub that represents this website. Then provide the website files. Use this exact format:
+
+ ---domain---
+ (domainscroll.pub here)
+ ---index.scroll---
+ buildHtml
+ baseUrl https://(domainscroll.pub here)
+ metaTags
+ editButton /edit.html
+ title (Title here)
+ style.css
+
+ (body content here. no blank lines please.)
+
+ script.js
+ ---style.css---
+ (CSS content here)
+ ---script.js---
+ (JavaScript content here)
+ ---end---
script.js
Changed around line 1
+ // Generate random PCA-like data
+ function generateRandomLeaders(num) {
+ const leaders = [];
+ for (let i = 0; i < num; i++) {
+ leaders.push({
+ x: Math.random() * 2 - 1,
+ y: Math.random() * 2 - 1,
+ name: `Leader ${i + 1}`,
+ traits: {
+ authoritarianism: Math.random(),
+ corruption: Math.random(),
+ charisma: Math.random(),
+ longevity: Math.random()
+ }
+ });
+ }
+ return leaders;
+ }
+
+ // Initialize plot
+ function initPlot() {
+ const canvas = document.getElementById('leaderPlot');
+ const ctx = canvas.getContext('2d');
+ const leaders = generateRandomLeaders(200);
+
+ // Draw points
+ leaders.forEach(leader => {
+ const x = (leader.x + 1) * canvas.width / 2;
+ const y = (leader.y + 1) * canvas.height / 2;
+
+ ctx.beginPath();
+ ctx.arc(x, y, 3, 0, 2 * Math.PI);
+ ctx.fillStyle = '#ff4b2b';
+ ctx.fill();
+ });
+
+ // Find match functionality
+ document.getElementById('findMatch').addEventListener('click', () => {
+ const input = document.getElementById('leaderTraits').value.toLowerCase();
+ const match = findClosestMatch(input, leaders);
+ document.getElementById('matchResult').textContent = `Closest match: ${match.name}`;
+ });
+ }
+
+ // Simple matching algorithm
+ function findClosestMatch(input, leaders) {
+ // Convert input to trait scores (very basic implementation)
+ const inputTraits = {
+ authoritarianism: input.includes('authoritarian') ? 1 : 0,
+ corruption: input.includes('corrupt') ? 1 : 0,
+ charisma: input.includes('charismatic') ? 1 : 0,
+ longevity: input.includes('long') ? 1 : 0
+ };
+
+ // Find closest match
+ let closest = leaders[0];
+ let minDistance = Infinity;
+
+ leaders.forEach(leader => {
+ const distance = Math.sqrt(
+ Math.pow(leader.traits.authoritarianism - inputTraits.authoritarianism, 2) +
+ Math.pow(leader.traits.corruption - inputTraits.corruption, 2) +
+ Math.pow(leader.traits.charisma - inputTraits.charisma, 2) +
+ Math.pow(leader.traits.longevity - inputTraits.longevity, 2)
+ );
+
+ if (distance < minDistance) {
+ minDistance = distance;
+ closest = leader;
+ }
+ });
+
+ return closest;
+ }
+
+ // Initialize when DOM is loaded
+ document.addEventListener('DOMContentLoaded', initPlot);
style.css
Changed around line 1
+ :root {
+ --gradient-primary: linear-gradient(135deg, #ff416c, #ff4b2b);
+ --gradient-secondary: linear-gradient(135deg, #4776e6, #8e54e9);
+ --text-primary: #ffffff;
+ --text-secondary: #e0e0e0;
+ --background-dark: #1a1a1a;
+ --background-light: #2d2d2d;
+ --accent-color: #ff4b2b;
+ }
+
+ body {
+ background: var(--background-dark);
+ color: var(--text-primary);
+ font-family: 'Segoe UI', sans-serif;
+ margin: 0;
+ padding: 0;
+ line-height: 1.6;
+ }
+
+ .hero {
+ background: var(--gradient-primary);
+ padding: 4rem 2rem;
+ text-align: center;
+ }
+
+ .logo {
+ font-size: 2rem;
+ font-weight: bold;
+ margin-bottom: 1rem;
+ }
+
+ .hero-content h1 {
+ font-size: 3rem;
+ margin-bottom: 1rem;
+ }
+
+ .pca-plot {
+ padding: 2rem;
+ background: var(--background-light);
+ }
+
+ .plot-container {
+ width: 90%;
+ max-width: 800px;
+ margin: 0 auto;
+ height: 500px;
+ }
+
+ canvas {
+ width: 100%;
+ height: 100%;
+ background: var(--background-dark);
+ border-radius: 10px;
+ }
+
+ .leader-input {
+ padding: 2rem;
+ text-align: center;
+ }
+
+ .input-container {
+ max-width: 600px;
+ margin: 0 auto;
+ }
+
+ input[type="text"] {
+ width: 100%;
+ padding: 1rem;
+ border: none;
+ border-radius: 5px;
+ margin-bottom: 1rem;
+ background: var(--background-light);
+ color: var(--text-primary);
+ }
+
+ button {
+ background: var(--accent-color);
+ color: white;
+ padding: 1rem 2rem;
+ border: none;
+ border-radius: 5px;
+ cursor: pointer;
+ transition: transform 0.2s;
+ }
+
+ button:hover {
+ transform: scale(1.05);
+ }
+
+ .match-result {
+ margin-top: 2rem;
+ padding: 1rem;
+ background: var(--background-light);
+ border-radius: 5px;
+ }
+
+ @media (max-width: 768px) {
+ .hero-content h1 {
+ font-size: 2rem;
+ }
+
+ .plot-container {
+ height: 300px;
+ }
+ }