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  1. LoanshieldLoanshieldPublic

    A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python

  2. langgraph-deep-researchlanggraph-deep-researchPublic

    A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook

  3. rag-playgroundrag-playgroundPublic

    A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python

  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic

    Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python

  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic

    Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python

  6. TweetLensTweetLensPublic

    Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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  1. LoanshieldLoanshieldPublic
    
A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python
  2. langgraph-deep-researchlanggraph-deep-researchPublic
    
A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook
  3. rag-playgroundrag-playgroundPublic
    
A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python
  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic
    
Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python
  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic
    
Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python
  6. TweetLensTweetLensPublic
    
Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Pinned
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  1. LoanshieldLoanshieldPublic
    
A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python
  2. langgraph-deep-researchlanggraph-deep-researchPublic
    
A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook
  3. rag-playgroundrag-playgroundPublic
    
A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python
  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic
    
Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python
  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic
    
Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python
  6. TweetLensTweetLensPublic
    
Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Pinned
Loading
  1. LoanshieldLoanshieldPublic
    
A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python
  2. langgraph-deep-researchlanggraph-deep-researchPublic
    
A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook
  3. rag-playgroundrag-playgroundPublic
    
A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python
  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic
    
Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python
  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic
    
Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python
  6. TweetLensTweetLensPublic
    
Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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Pinned
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  1. LoanshieldLoanshieldPublic
    
A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python
  2. langgraph-deep-researchlanggraph-deep-researchPublic
    
A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook
  3. rag-playgroundrag-playgroundPublic
    
A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python
  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic
    
Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python
  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic
    
Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python
  6. TweetLensTweetLensPublic
    
Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Pinned
Loading
  1. LoanshieldLoanshieldPublic
    
A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python
  2. langgraph-deep-researchlanggraph-deep-researchPublic
    
A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook
  3. rag-playgroundrag-playgroundPublic
    
A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python
  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic
    
Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python
  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic
    
Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python
  6. TweetLensTweetLensPublic
    
Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Pinned
Loading
  1. LoanshieldLoanshieldPublic
    
A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python
  2. langgraph-deep-researchlanggraph-deep-researchPublic
    
A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook
  3. rag-playgroundrag-playgroundPublic
    
A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python
  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic
    
Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python
  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic
    
Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python
  6. TweetLensTweetLensPublic
    
Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Pinned
Loading
  1. LoanshieldLoanshieldPublic
    
A Multi-Agent Framework for Compliant, Real-Time Automated Lending Risk Analysis

    Python
  2. langgraph-deep-researchlanggraph-deep-researchPublic
    
A modular agentic research system that first scopes user intent into a structured research brief, then performs deep web research to gather, filter, and synthesize insights.

    Jupyter Notebook
  3. rag-playgroundrag-playgroundPublic
    
A hands-on sandbox for experimenting with Retrieval-Augmented Generation (RAG) workflows using modern LLM, embeddings, and vector databases.

    Python
  4. Handwriting-in-the-VoidHandwriting-in-the-VoidPublic
    
Real-time air handwriting recognition using computer vision and an MLP model, enabling users to write alphabets in the air and get instant prediction

    Python
  5. TimeSeries-Forecasting-LabTimeSeries-Forecasting-LabPublic
    
Time series forecasting using classical statistical models to analyze trends, seasonality and temporal patterns. Multiple ML models are evaluated to identify the most effective forecasting approach.

    Python
  6. TweetLensTweetLensPublic
    
Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

    Python