Questgen
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Quizlet
Quizbot
PrepAI
Meiro
LARQ
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GitHub
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BitBucket
VS Code
Git
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Questgen is an AI quiz generator that creates various types of quizzesโsuch as Multiple Choice Questions (MCQs), True/False Questions, Fill-in-the-Blank, Higher-Order Thinking Questions, Match-the-Following, and Bloomโs Taxonomy-based quizzesโwith just one click. You can edit and customize the generated worksheet before exporting it in multiple available formats, including PDF, QTI, Moodle XML, CSV, and plain text. Questgen is ideal for teachers, students, schools, and HR teams looking to create or practice quizzes at scale.
Questgen GitHubBased on our record, GitHub seems to be more popular. It has been mentiond 2466 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
// ==UserScript== // @name GitHub -> Obsidian Task // @namespace obsidian // @version 1.0 // @match https://github.com/*/*/issues/* // @match https://github.com/*/*/pull/* // @grant GM_setClipboard // ==/UserScript== (function () { 'use strict'; function getTitle() { return document.querySelector("bdi")?.textContent.trim(); } function copyTask() { ... - Source: dev.to / about 8 hours ago
Import requests From bs4 import BeautifulSoup From datetime import datetime Def fetch_github_trending(): url = "https://github.com/trending?since=daily" response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') repos = [] for article in soup.select('article.Box-row'): repo_link = article.select_one('h2 a')['href'] stars_today =... - Source: dev.to / 1 day ago
Git clone https://github.com//.git /opt/app Cd /opt/app Docker build -t app . Docker run -d --name app --restart unless-stopped -p 8080:8080 app. - Source: dev.to / 5 days ago
The core of the ecosystem is the official open-source server hosted on GitHub. It is written in TypeScript and implements the full MCP specification. - Source: dev.to / 9 days ago
This is why the gate needs a trace it can trust, and why AgentLens is the other half of this workflow. agent-eval scores and gates the output; AgentLens captures the trace of how the agent got there โ every model call and tool step, the resolved inputs (not the templated ones), the raw outputs. That trace is exactly the unforgeable, agent-didn't-author substrate that Tier 1+2 need to score against. Without it,... - Source: dev.to / 10 days ago
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