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Yaw – A terminal built around the Claude Code/Codex CLI workflow

Yaw – A terminal built around the Claude Code/Codex CLI workflow

by tkjef·Mar 3, 2026·4 points·6 comments

AI Analysis

●●SolidSolve My ProblemSlick

Auto-split pane for Claude Code + shell eliminates 50-times-a-day context switching.

Strengths
  • Auto-snap workflow is genuinely clever—detects AI CLI launch and splits pane by magic, real DX win
  • Connection manager consolidates SSH, six databases, and encrypted credentials in one place
  • Multi-LLM chat panel with terminal context is table stakes but well-executed
Weaknesses
  • Electron overhead for a terminal—bloated vs Warp, iTerm2, or native alternatives
  • No differentiation on core terminal features (tabs, splits, WebGL rendering are standard)
  • Tailscale integration is handy but narrow—relies on specific infra choices users may not have made
Target Audience

AI-assisted developers using Claude Code/Codex, terminal power users, DevOps engineers managing remote connections

Similar To

Warp · Cursor IDE · Continue (VS Code extension for Claude Code)

Post Description

I use Claude Code and Codex constantly, and my workflow was always the same: launch the agent, need a shell in the same directory, open a new tab, cd back. Fifty times a day.

So I built auto-snap into Yaw — launch any AI coding CLI and it detects it and splits the pane automatically. Agent on the left, fresh shell in the same directory on the right. Works with Claude Code, Codex, Gemini CLI, and Vibe CLI. You can install any of them through a built-in wizard.

Yaw is also a full terminal (tabs, split panes, broadcast, search, session restore, WebGL via xterm.js) with a built-in connection manager for SSH, PostgreSQL, MySQL, SQL Server, MongoDB, and Redis — encrypted credentials, Tailscale auto-detection, remote Screen session management. And a chat panel that sends terminal output as context to Claude, ChatGPT, Gemini, Ollama, and six other providers.

Electron + xterm.js + React. v0.9.75, Windows and macOS.

Curious what other people's AI coding CLI setups look like — what's working, what's missing?

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