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Source channel @githubtrending · Post #15417 · Jan 16

#shell OpenCode now supports Claude Max/Pro subscriptions through the `opencode-anthropic-auth` plugin, allowing you to use your Claude subscription with both Claude Code and OpenCode in your terminal. This integration works with Gentleman.Dots, a complete development environment configuration that includes Neovim with AI assistants, multiple shells (Fish, Zsh, Nushell), terminal multiplexers (Tmux, Zellij), and various terminal emulators. You can install it via Homebrew or direct download across macOS, Linux, and Android platforms. The setup includes an interactive TUI installer that automatically configures your preferred tools, plus a Vim Mastery Trainer for learning editor shortcuts through progressive lessons and boss fights. This gives you a fully integrated AI-powered coding environment optimized for terminal-based development workflows. https://github.com/Gentleman-Programming/Gentleman.Dots

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@githubtrending · Post #15523 · 02/25/2026, 12:30 PM

#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