#javascript #agentic_ai #agentic_engineering #agentic_framework #agentic_rag #agentic_workflow #ai_assistant #ai_tools #anthropic_claude #autonomous_agents #claude_code #codex #huggingface #jules #mcp_server #model_context_protocol #multi_agent #multi_agent_systems #npx #swarm #swarm_intelligence

Claude-Flow v2.7 is an enterprise AI platform with hive-mind swarms, 25 natural language skills, 100+ tools, and AgentDB integration for 96x-164x faster semantic search and 4-32x less memory use. Install via `npx claude-flow@alpha init` after Claude Code, then use commands like `swarm "build API"` for quick tasks or hive-mind for projects. It boosts your coding speed with 84.8% problem-solving rate, automation, GitHub tools, and persistent memory—saving you hours on complex development.

https://github.com/ruvnet/claude-flow

#javascript #agent #agentic #agentic_ai #ai #ai_agents #automation #cursor #design #figma #generative_ai #llm #llms #mcp #model_context_protocol

Cursor Talk to Figma MCP lets Cursor AI read and edit your Figma designs directly, using tools like `get_selection` for info, `set_text_content` for bulk text changes, `create_rectangle` for shapes, and `set_instance_overrides` for components. Setup is quick: install Bun, run `bun setup` and `bun socket`, add the Figma plugin. This saves you hours by skipping context switches, automating repetitive tasks like text replacement or override propagation, speeding up design-to-code workflows, and keeping everything in sync for faster, precise builds.

https://github.com/grab/cursor-talk-to-figma-mcp

#python #agentic_ai #agents #ai #ai_agents #realtime #stt #tts #video_agents #video_ai #vision_ai #voice_ai

Vision Agents is an open-source Python framework by Stream to build real-time AI agents that watch video, listen to audio, and respond instantly with low latency under 30ms. It integrates YOLO, Roboflow, OpenAI, Gemini, and 25+ tools for apps like golf coaching, security cameras detecting theft, or phone assistants. Install easily with `uv add vision-agents`, use free Stream credits, and deploy on any video network. You benefit by quickly creating smart video AI for gaming, safety, or coaching without vendor lock-in, saving time and costs on custom builds.

https://github.com/GetStream/Vision-Agents

#typescript #agentic_workflow #ai_agent #ai_runtime #ai_sandbox #claude_code #cli #cloudflare #codex #containers #context_engineer #dev_tools #gemini_cli #react #sandbox #typescript

VM0 is a natural language agent that runs workflows automatically 24/7 in secure cloud sandboxes. It offers isolated Claude Code execution, 35,000+ skills for tools like GitHub and Notion, persistent chats with resume/fork options, and full logs/metrics for monitoring. Quick start via `npm install -g @vm0/cli && vm0 onboard` gets you automating in 5 minutes. You benefit by saving hours on repetitive tasks like reports or data syncs, with reliable, observable runs anytime.

https://github.com/vm0-ai/vm0

#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

#typescript #agentic_ai #ai_agents #claude_code #cli #codex #coding_agents #cursor_agent #desktop_app #developer_tools #electron #git_worktree #llm #mcp #opencode #orchestration #parallel_agents #terminal #tui #vibe_coding #worktrees

Superset is a turbocharged macOS terminal for running 10+ CLI coding agents like Claude Code, Cursor, and GitHub Copilot in parallel. It isolates tasks in separate Git worktrees to avoid interference, lets you monitor progress from one dashboard, review changes with a built-in diff viewer, and switch contexts quickly. You benefit by coding 10x faster, shipping more without context-switching delays or conflicts, saving time on development workflows.

https://github.com/superset-sh/superset

#python #agentic_ai #agentic_coding #ai_coding_agent #ai_plugins #anthropic_claude #claude_ai #claude_ai_skills #claude_code #claude_code_plugins #claude_code_skills #claude_skills #claudecode_subagents #developer_tools #devtools #mcp_tools #openai_codex #prompt_engineering

Claude Code Skills offers 169 free, ready-to-use plugins that turn AI coding agents like Claude Code, OpenAI Codex, and OpenClaw into experts in engineering, marketing, product, compliance, and more. Install easily via simple commands to add skills like security auditing, test automation, or C-level advice, with 160+ Python tools included. This saves you time by automating complex tasks, boosting code quality, and handling grunt work so you focus on creative problem-solving and faster results.

https://github.com/alirezarezvani/claude-skills

#python #agentic_ai #agents #memory

Hindsight is a top agent memory system that helps AI agents learn over time by storing facts, experiences, and mental models like human memory, beating rivals on LongMemEval benchmarks with 91.4% accuracy. Add it easily with 2 lines of code via Python or Node.js clients, using simple retain, recall, and reflect operations for Docker or embedded setups. You benefit by building smarter, consistent agents that reduce errors, cut hallucinations, handle long-term tasks, and personalize chats—saving time and boosting performance in production.

https://github.com/vectorize-io/hindsight

#python #agent #agentic_rag #ai_agents #clawbot #context_database #context_engineering #filesystem #llm #memory #openclaw #opencode #rag #skill

OpenViking is a free open-source tool that acts as a context database for AI agents, using a simple file system to organize memories, resources, and skills under viking:// paths. It fixes issues like scattered data, high token costs, weak searches, and untraceable errors with tiered loading (L0 abstracts, L1 overviews, L2 details loaded on demand), recursive directory retrieval, visual traces, and auto-session memory updates. You benefit by building smarter, cheaper agents faster—like managing files—saving up to 96% on tokens while boosting task success by 50%+.

https://github.com/volcengine/OpenViking

#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