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Show HN: AI Harness that lets a graph of Codex and Claude intercommunicate Show HN:AI 工具链,让 Codex 和 Claude 的图结构相互通信

Rysh CLI is an agentic terminal multiplexer written in Go that combines familiar terminal navigation (tabs, panes, splits, vim/htop) with AI agent capabilities in every pane Each pane can independently run AI agents (Claude, Codex) that answer prompts and call tools, with sessions persisting as daemons across restarts Supports multi-agent parallel workflows with cross-vendor agent orchestration (e.g., Claude and Codex working side-by-side in stacked panes) Includes SecretNAT for security: secret Rysh是用Go编写的智能终端多路复用器,将传统终端功能(标签页、窗格、分割)与AI agent能力深度融合 每个终端窗格都是独立agent,支持Claude、Codex等多提供商并行工作,实现多agent协作任务处理 会话采用daemon持久化模式,重启后agent状态和记忆完整保留,突破传统终端会话限制 内置SecretNAT安全机制,请求发出前自动替换敏感信息为token,本地可逆还原,模型仅见token 支持agent fleet图结构编排,通过消息传递实现任务分发、并行执行、结果汇总的完整工作流

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Hot 热度
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Quality 质量
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Impact 影响力

Analysis 深度分析

TL;DR

  • Rysh CLI is an agentic terminal multiplexer written in Go that combines familiar terminal navigation (tabs, panes, splits, vim/htop) with AI agent capabilities in every pane
  • Each pane can independently run AI agents (Claude, Codex) that answer prompts and call tools, with sessions persisting as daemons across restarts
  • Supports multi-agent parallel workflows with cross-vendor agent orchestration (e.g., Claude and Codex working side-by-side in stacked panes)
  • Includes SecretNAT for security: secrets are tokenized before leaving the machine, with reversible local mapping so models never see plaintext credentials
  • Agent fleets can be designed as graphs with directed edges representing communication paths, enabling hierarchical task delegation and parallel execution

Why It Matters

This represents a significant evolution in how developers interact with AI agents—moving from single-agent chat interfaces to multi-agent terminal environments where agents can collaborate, delegate, and work in parallel. For AI practitioners, it demonstrates a practical architecture for orchestrating multiple LLM calls with persistent state, secure credential handling, and graph-based workflow design.

Technical Details

  • Architecture: Go-based terminal multiplexer with daemon-persisted sessions; agents survive session restarts and maintain context (demonstrated via codeword recall)
  • Multi-agent orchestration: Supports running multiple agents from different vendors (Claude, Codex) simultaneously in stacked panes, with Ctrl+S navigation and parallel file generation
  • Graph-based fleet design: Agent organizations are modeled as directed graphs where edges define communication paths; orders travel down as messages, results bubble up on a shared board
  • SecretNAT security: On-by-default secret substitution replaces credentials with tokens in outbound requests; responses with plaintext credentials are reported to panes but not rewritten; local reversible mapping via ##snat get <token>
  • Dual binary distribution: rysh (open-source, Apache-2.0) and ry (prebuilt commercial distribution) are separate; requires Go 1.25.3+ for source builds; WSL2 supported on Windows

Industry Insight

  • The daemon-based session model (vs. ephemeral terminal sessions) enables persistent agent state, which is critical for long-running multi-agent workflows that need to survive interruptions—this could become a standard pattern for production agent orchestration
  • The graph-based agent topology (with explicit edges defining inter-agent communication) provides a programmable abstraction for complex multi-agent systems, moving beyond flat prompt chains to structured organizational designs
  • SecretNAT's approach of tokenizing secrets at the client side before they reach LLM APIs addresses a growing security concern in AI adoption; this client-side secret management pattern could influence how future AI tools handle credential security by default

TL;DR

  • Rysh是用Go编写的智能终端多路复用器,将传统终端功能(标签页、窗格、分割)与AI agent能力深度融合
  • 每个终端窗格都是独立agent,支持Claude、Codex等多提供商并行工作,实现多agent协作任务处理
  • 会话采用daemon持久化模式,重启后agent状态和记忆完整保留,突破传统终端会话限制
  • 内置SecretNAT安全机制,请求发出前自动替换敏感信息为token,本地可逆还原,模型仅见token
  • 支持agent fleet图结构编排,通过消息传递实现任务分发、并行执行、结果汇总的完整工作流

为什么值得看

Rysh代表了终端工具与AI agent融合的前沿探索,为开发者提供了在熟悉终端环境中直接调用多个AI agent进行并行任务处理的创新方案。其daemon会话模型和agent协作架构为复杂开发工作流提供了工程化实践参考。

技术解析

  • 架构设计:基于Go语言开发,采用daemon会话模式而非传统终端模式,实现agent状态的持久化保存和跨会话记忆保持
  • 多agent并行:支持在同一窗口中同时运行多个agent实例,可混合使用Claude和Codex等不同提供商,通过Ctrl+S+数字键切换窗格
  • 协作机制:通过图结构组织agent关系,orders沿边向下传递消息,results沿边向上返回,支持manager-worker模式的任务分发与结果汇总
  • 安全特性:SecretNAT默认启用,在请求离开机器前将敏感信息替换为token,响应中的明文凭证会在窗格中报告但不重写,本地可通过##snat get <token>还原
  • 跨平台支持:WSL2为官方支持路径,Windows可编译运行但无法打开pane,两个独立二进制rysh(开源Apache-2.0)和ry(预构建产品)

行业启示

  • 终端工具正从操作界面演变为AI agent交互载体,代表人机交互范式从"人驱动工具"向"人协调agent"转变
  • 多agent协作架构通过图结构实现任务编排,为复杂开发工作流的分布式处理提供了可落地的工程方案
  • 安全与便利的平衡设计(SecretNAT)展示了AI工具在敏感信息处理上的创新思路,值得同类工具借鉴

Disclaimer: The above content is generated by AI and is for reference only. 免责声明:以上内容由 AI 生成,仅供参考。

Claude Claude Code Generation 代码生成 Agent Agent Open Source 开源 LLM 大模型