#html #ech #fail2ban #http #mixed #ml_dsa_65 #ml_kem_768 #post_quantum #reality #shadowsocks #shadowsocks2022 #tls #trojan #tunnel #vless #vmess #wireguard #x25519 #xtls_rprx_vision #xtls_rprx_vision_udp443

3X-UI is an easy-to-use, open-source web control panel for managing Xray-core VPN servers. It supports many VPN protocols like VMess, VLESS, Shadowsocks, Trojan, and WireGuard, letting you configure, monitor traffic, manage users, and set limits through a simple web interface. It includes features like automatic SSL certificates, traffic statistics, multi-user support, and security options such as firewall rules and IP bans. This makes managing VPN servers faster, more secure, and accessible even if you are not an expert, helping you control your VPN setup efficiently and safely.

https://github.com/MHSanaei/3x-ui

#html

The Agent Development Kit (ADK) is an open-source toolkit that helps you build, test, and deploy advanced AI agents easily. It lets you create flexible, multi-agent systems using Python or Java, supports many AI models, and works with different deployment options. ADK offers a rich set of tools, built-in monitoring, and simple integration with Google services, making it easier to develop, debug, and scale your AI applications. This means you can focus on creating smart, efficient agents without worrying about complex setup or compatibility issues.

https://github.com/google/adk-docs

#html #ai_agent_tools #ai_agents #ai_tools #code_execution #code_executor #code_runner #competitive_programming #online_compiler #online_judge #online_judges #onlinejudge #onlinejudge_solution

Judge0 is a free, open-source tool that safely runs code from over 90 languages online. It's fast, scalable, and sandboxed for AI agents, coding platforms, e-learning, and job tests. Use its simple API or Python SDK to execute code easily—self-host it or try the cloud. This helps you build apps quickly without managing servers, saving time and ensuring secure code testing.

https://github.com/judge0/judge0

#html #agentic_engineering #best_practices #claude_ai #claude_code #vibe_coding

To master Claude Code effectively, create a CLAUDE.md file that documents your project's overview, key commands, coding standards, and workflows. This file prevents Claude from repeatedly scanning your codebase and ensures consistent behavior across sessions. Include hooks that automatically format code and run type checks after edits, and organize instructions into commands, agents, and skills for different tasks. Keep your CLAUDE.md concise—under 200 lines—since overly long files cause Claude to ignore important rules. Use plan mode before implementation, write detailed specs to reduce ambiguity, and leverage subagents for parallel work to maintain a clean main context. The benefit: you'll accelerate development speed while maintaining code quality and consistency, allowing Claude to work more autonomously with fewer corrections needed.

https://github.com/shanraisshan/claude-code-best-practice

#java #a11y #accessibility #ai #bounding_box #document_parsing #eaa #html #json #markdown #ocr #ocr_recognition #pdf #pdf_accessibility #pdf_converter #pdf_extraction #pdf_parser #pdf_ua #rag #tables #tagged_pdf

OpenDataLoader PDF is a free, open-source tool (Apache 2.0) that tops benchmarks with 0.90 accuracy for extracting structured data like Markdown, JSON (with bounding boxes), and HTML from any PDF—digital, scanned, or complex with tables, formulas, charts, and OCR in 80+ languages. It runs locally on CPU (0.05s/page fast mode), filters AI prompt injections for safety, integrates with LangChain/RAG, and automates accessibility tagging to Tagged PDF. You save time and costs on parsing for AI pipelines or compliance (vs. $50–200/manual doc), getting precise, private results for better LLM apps and legal standards.

https://github.com/opendataloader-project/opendataloader-pdf

#html

ArcKit is an AI toolkit for enterprise architects. It creates structured workflows for governance, requirements, risks, data models, vendor RFPs, diagrams, and UK government compliance like GDS and GDPR. Install via Claude Code plugin, Gemini CLI, or pip, then use commands like `/arckit.requirements` or `/arckit.risk`. This saves weeks of manual work, enforces traceability, reduces errors, and produces audit-ready docs—helping you deliver better projects faster with less scattered files.

https://github.com/tractorjuice/arc-kit

#html #claude_code #claude_code_plugin #harness #harness_engineering

Harness is a Claude Code plugin that builds agent teams and skills for your project from one simple prompt, using six team patterns like pipeline, supervisor, and fan-out/fan-in. It helps you turn a domain idea into organized agents, better coordination, and tested outputs, so you can save time and handle complex work more reliably.

https://github.com/revfactory/harness

#html #awesome #awesome_list #generative_ai #interview_questions #large_language_models #llms #notebook_jupyter #vision_and_language

This guide is a free, one-stop place for generative AI learning. It gives you papers, courses, roadmaps, interview prep, code notebooks, and tools, so you can quickly learn the basics, build apps, and prepare for jobs. It helps you save time by putting many useful resources in one place and showing what to study next.

https://github.com/aishwaryanr/awesome-generative-ai-guide

#typescript #ai #animation #ffmpeg #framework #gsap #html #mcp #puppeteer #rendering #typescript #video

HyperFrames is an open-source tool that turns HTML, CSS, media, and animations into MP4 videos. You can use it with the CLI or with AI coding agents, and the same input makes the same video every time, which helps with previewing, testing, and automated production. This benefits you by letting you make editable, web-style videos faster without learning a new video editor, while keeping the output reliable and easy to render locally.

https://github.com/heygen-com/hyperframes

#html #excercises #fitness #fitness_app

This dataset provides 1,324 fitness exercises with step-by-step instructions in six languages, plus tools to build your own workout app backend. While it includes all text data and metadata, it does not bundle GIFs or images due to ownership claims, so you must add your own media. The benefit is a ready-made, multilingual foundation that saves you months of data collection and coding, letting you launch a professional fitness app or AI coach quickly without needing to recreate the exercise database from scratch.

https://github.com/hasaneyldrm/exercises-dataset