#javascript #agents #ai #ai_agents #automation #claude #cli #development #framework #fullstack #nodejs #orchestration #typescript
Synkra AIOS is an AI-powered development framework that automates software creation through specialized agents working together in coordinated teams. It uses a two-phase approach: planning agents (analyst, PM, architect) create detailed project specifications, then development agents (Scrum Master, developer, QA) execute those plans with full context preserved throughout. The framework prioritizes CLI-first operations with observability and UI as secondary layers, eliminating common problems like planning inconsistency and context loss in AI-assisted development. You benefit from faster, more coherent project delivery with autonomous agents handling planning, coding, and quality assurance while maintaining architectural consistency and reducing manual coordination overhead.
https://github.com/SynkraAI/aios-core
Synkra AIOS is an AI-powered development framework that automates software creation through specialized agents working together in coordinated teams. It uses a two-phase approach: planning agents (analyst, PM, architect) create detailed project specifications, then development agents (Scrum Master, developer, QA) execute those plans with full context preserved throughout. The framework prioritizes CLI-first operations with observability and UI as secondary layers, eliminating common problems like planning inconsistency and context loss in AI-assisted development. You benefit from faster, more coherent project delivery with autonomous agents handling planning, coding, and quality assurance while maintaining architectural consistency and reducing manual coordination overhead.
https://github.com/SynkraAI/aios-core
GitHub
GitHub - SynkraAI/aios-core: Synkra AIOS: AI-Orchestrated System for Full Stack Development - Core Framework v4.0
Synkra AIOS: AI-Orchestrated System for Full Stack Development - Core Framework v4.0 - SynkraAI/aios-core
#typescript #ai_agents #ai_assistant #ai_coding #ai_coding_tools #ai_engineering #ai_tools #anthropic #anthropic_claude #claude #claude_ai #claude_code #claude_context #claude_mem #claude_skills #claudecode #mcp #model_context_protocol #software_engineering #spec_driven_development
Claude Pilot enhances Claude Code by enforcing production-grade quality automatically. It adds mandatory testing, automatic code formatting and type checking, and persistent memory across sessions so your AI assistant maintains context on complex projects. Instead of babysitting Claude's output, you start a task, grab coffee, and return to verified, tested code ready to ship—saving hours on manual review and catching bugs before they reach production.
https://github.com/maxritter/claude-pilot
Claude Pilot enhances Claude Code by enforcing production-grade quality automatically. It adds mandatory testing, automatic code formatting and type checking, and persistent memory across sessions so your AI assistant maintains context on complex projects. Instead of babysitting Claude's output, you start a task, grab coffee, and return to verified, tested code ready to ship—saving hours on manual review and catching bugs before they reach production.
https://github.com/maxritter/claude-pilot
GitHub
GitHub - maxritter/pilot-shell: The professional development environment for Claude Code. Claude Code is powerful. Pilot Shell…
The professional development environment for Claude Code. Claude Code is powerful. Pilot Shell makes it reliable. Start a task, grab a coffee, come back to production-grade code. Tests enforced. Co...
#typescript #ai #cli #summarize #typescript
Summarize is a fast tool for summarizing URLs, PDFs, images, audio/video, YouTube, and podcasts via Chrome Side Panel (with chat and history), Firefox Sidebar, or CLI. Install the extension from Chrome Web Store, add the local daemon with `npm i -g @steipete/summarize` and `summarize daemon install --token <TOKEN>`, then get one-click summaries, YouTube slides with OCR/timestamps, streaming Markdown, and media transcription. It saves time by quickly digesting long content so you focus on key insights without reading everything.
https://github.com/steipete/summarize
Summarize is a fast tool for summarizing URLs, PDFs, images, audio/video, YouTube, and podcasts via Chrome Side Panel (with chat and history), Firefox Sidebar, or CLI. Install the extension from Chrome Web Store, add the local daemon with `npm i -g @steipete/summarize` and `summarize daemon install --token <TOKEN>`, then get one-click summaries, YouTube slides with OCR/timestamps, streaming Markdown, and media transcription. It saves time by quickly digesting long content so you focus on key insights without reading everything.
https://github.com/steipete/summarize
GitHub
GitHub - steipete/summarize: Point at any URL/YouTube/Podcast or file. Get the gist. CLI and Chrome Extension.
Point at any URL/YouTube/Podcast or file. Get the gist. CLI and Chrome Extension. - steipete/summarize
#go #ai_agents #ai_security_tool #anthropic #autonomous_agents #golang #gpt #graphql #multi_agent_system #offensive_security #open_source #openai #penetration_testing #penetration_testing_tools #react #security_automation #security_testing #security_tools #self_hosted
PentAGI is an AI-powered tool that automates penetration testing with smart agents using 20+ pro tools like nmap and metasploit in a safe Docker sandbox. It researches vulnerabilities, executes attacks, stores knowledge for reuse, and creates detailed reports via a simple web UI. Quick setup needs Docker, an LLM API key (OpenAI/Anthropic), and `docker compose up -d`. This saves you hours of manual work, speeds up secure testing, cuts errors, and helps find issues faster for better protection.
https://github.com/vxcontrol/pentagi
PentAGI is an AI-powered tool that automates penetration testing with smart agents using 20+ pro tools like nmap and metasploit in a safe Docker sandbox. It researches vulnerabilities, executes attacks, stores knowledge for reuse, and creates detailed reports via a simple web UI. Quick setup needs Docker, an LLM API key (OpenAI/Anthropic), and `docker compose up -d`. This saves you hours of manual work, speeds up secure testing, cuts errors, and helps find issues faster for better protection.
https://github.com/vxcontrol/pentagi
GitHub
GitHub - vxcontrol/pentagi: ✨ Fully autonomous AI Agents system capable of performing complex penetration testing tasks
✨ Fully autonomous AI Agents system capable of performing complex penetration testing tasks - vxcontrol/pentagi
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#rust #ai #ai_ocr #attention_mechanism #gnn #gnn_model #gnns #graph #graph_neural_networks #llm_inference #low_latency #mincut #neo4j #ocr #onnx #rust #vector #wasm
RuVector is a free, open-source vector database that gets smarter with every query. Unlike static databases, it learns from usage via GNN layers, runs LLMs locally with no cloud costs, supports graph queries like Neo4j, scales freely across nodes, and deploys as a single self-booting file (125ms startup). Run with `npx ruvector`. You benefit from faster, more accurate AI search that improves automatically, zero operating costs, full offline/privacy control, and easy scaling—perfect for RAG, agents, or edge apps without vendor lock-in.
https://github.com/ruvnet/ruvector
RuVector is a free, open-source vector database that gets smarter with every query. Unlike static databases, it learns from usage via GNN layers, runs LLMs locally with no cloud costs, supports graph queries like Neo4j, scales freely across nodes, and deploys as a single self-booting file (125ms startup). Run with `npx ruvector`. You benefit from faster, more accurate AI search that improves automatically, zero operating costs, full offline/privacy control, and easy scaling—perfect for RAG, agents, or edge apps without vendor lock-in.
https://github.com/ruvnet/ruvector
GitHub
GitHub - ruvnet/ruvector: RuVector is a High Performance, Real-Time, Self-Learning, Vector Graph Neural Network, and Database built…
RuVector is a High Performance, Real-Time, Self-Learning, Vector Graph Neural Network, and Database built in Rust. - ruvnet/ruvector
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#python #ai #ai_scraping #automation #crawler #crawling #crawling_python #data #data_extraction #mcp #mcp_server #playwright #python #scraping #selectors #stealth #web_scraper #web_scraping #web_scraping_python #webscraping #xpath
Scrapling is a fast Python web scraping tool that fetches pages, bypasses anti-bot blocks like Cloudflare, and adapts to site changes by auto-finding elements. Use simple CSS/XPath selectors, spiders for big crawls with pause/resume, proxy rotation, and CLI—no code needed sometimes. Install via pip; it's memory-light and beats others in speed. You save time fixing broken scrapers, scrape reliably at scale, cut costs with AI tools, and focus on using data for leads, prices, or research.
https://github.com/D4Vinci/Scrapling
Scrapling is a fast Python web scraping tool that fetches pages, bypasses anti-bot blocks like Cloudflare, and adapts to site changes by auto-finding elements. Use simple CSS/XPath selectors, spiders for big crawls with pause/resume, proxy rotation, and CLI—no code needed sometimes. Install via pip; it's memory-light and beats others in speed. You save time fixing broken scrapers, scrape reliably at scale, cut costs with AI tools, and focus on using data for leads, prices, or research.
https://github.com/D4Vinci/Scrapling
GitHub
GitHub - D4Vinci/Scrapling: 🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale…
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl! - D4Vinci/Scrapling
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#rust #ai_gateway #ai_gateway_support #envoy #envoyproxy #gateway #generative_ai #llm_gateway #llm_inference #llm_proxy #llm_routing #llmops #llms #openai #prompt #proxy #proxy_server #routing
Plano is an AI-native proxy server that handles key tasks for agentic apps like routing between agents, smart LLM model selection, safety guardrails, and automatic traces for observability. Define agents in simple YAML, write basic HTTP code in any language, and start Plano to run multi-agent systems without custom plumbing or framework lock-in. You benefit by building and shipping reliable agents to production much faster, focusing on core logic while gaining safety, low latency, and easy scaling.
https://github.com/katanemo/plano
Plano is an AI-native proxy server that handles key tasks for agentic apps like routing between agents, smart LLM model selection, safety guardrails, and automatic traces for observability. Define agents in simple YAML, write basic HTTP code in any language, and start Plano to run multi-agent systems without custom plumbing or framework lock-in. You benefit by building and shipping reliable agents to production much faster, focusing on core logic while gaining safety, low latency, and easy scaling.
https://github.com/katanemo/plano
GitHub
GitHub - katanemo/plano: Delivery infrastructure for agentic apps - Plano is an AI-native proxy and data plane that offloads plumbing…
Delivery infrastructure for agentic apps - Plano is an AI-native proxy and data plane that offloads plumbing work, so you stay focused on your agent's core logic (via any AI framework). - k...
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#javascript #ai #algorithm #artificial_intelligence #chatgpt #claude #cursor #deep_learning #deepseek #gemini #generative_ai #gpt #llm #mcp #openai #python #rag #vibe_coding #vibecoding #vue #vuepress
鱼皮的 AI知识库 offers a free Vibe Coding tutorial for beginners, teaching AI-powered programming with natural language prompts to build and monetize apps fast—no coding skills needed. It covers tools, projects, tips, and paths like making your first work in 10 minutes, plus AI guides on DeepSeek, Cursor, and more. You benefit by quickly creating profitable products, breaking tech barriers, and enjoying AI perks to improve life and work. Start at ai.codefather.cn/vibe.
https://github.com/liyupi/ai-guide
鱼皮的 AI知识库 offers a free Vibe Coding tutorial for beginners, teaching AI-powered programming with natural language prompts to build and monetize apps fast—no coding skills needed. It covers tools, projects, tips, and paths like making your first work in 10 minutes, plus AI guides on DeepSeek, Cursor, and more. You benefit by quickly creating profitable products, breaking tech barriers, and enjoying AI perks to improve life and work. Start at ai.codefather.cn/vibe.
https://github.com/liyupi/ai-guide
鱼皮AI导航
🌟 AI 编程零基础入门教程 Vibe Coding - 鱼皮的 AI 知识库(免费) - 鱼皮AI导航
# 鱼皮 Vibe Coding 零基础入门教程
大家好,我是程序员鱼皮。
如今 Vibe Coding 已经火遍全网,不仅是程序员,连设计师、产品运营、甚至完全不懂技术的人都开始用 Vibe C。鱼皮AI导航收录全球AI工具网站应用,专业学习资源资讯知识库,AI学习与交流社区。
大家好,我是程序员鱼皮。
如今 Vibe Coding 已经火遍全网,不仅是程序员,连设计师、产品运营、甚至完全不懂技术的人都开始用 Vibe C。鱼皮AI导航收录全球AI工具网站应用,专业学习资源资讯知识库,AI学习与交流社区。
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#typescript #agent #agentic #agentic_framework #agentic_workflow #ai #ai_agents #bytedance #deep_research #harness #langchain #langgraph #langmanus #llm #multi_agent #nodejs #podcast #python #superagent #typescript
DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge.
https://github.com/bytedance/deer-flow
DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge.
https://github.com/bytedance/deer-flow
GitHub
GitHub - bytedance/deer-flow: An open-source SuperAgent harness that researches, codes, and creates. With the help of sandboxes…
An open-source SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skills and subagents, it handles different levels of tasks that could take minute...
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#typescript #agent #agent_development #ai_agent #claude #claude_code #educational #llm #python #teaching #tutorial
Claude Code is an AI agent framework that uses a simple loop: send messages to Claude, check if it needs tools, execute those tools, and repeat. The benefit is that you can build powerful autonomous agents by layering one feature at a time—from basic tool use to multi-agent teams—without rewriting the core loop. This modular approach lets you start simple with bash commands and scale to complex workflows with planning, skill loading, background tasks, and team coordination, making it easier to automate development work and delegate entire projects to AI agents.
https://github.com/shareAI-lab/learn-claude-code
Claude Code is an AI agent framework that uses a simple loop: send messages to Claude, check if it needs tools, execute those tools, and repeat. The benefit is that you can build powerful autonomous agents by layering one feature at a time—from basic tool use to multi-agent teams—without rewriting the core loop. This modular approach lets you start simple with bash commands and scale to complex workflows with planning, skill loading, background tasks, and team coordination, making it easier to automate development work and delegate entire projects to AI agents.
https://github.com/shareAI-lab/learn-claude-code
GitHub
GitHub - shareAI-lab/learn-claude-code: Bash is all you need - A nano Claude Code–like agent, built from 0 to 1
Bash is all you need - A nano Claude Code–like agent, built from 0 to 1 - shareAI-lab/learn-claude-code
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