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│ ✻ Welcome to Claude Code!                         │
│                                                   │
│   /help for help, /status for your current setup  │
│                                                   │
│   cwd: /Users/badlogic/workspaces/tuicp           │
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> Read /Users/badlogic/workspaces/tuicp/evaluation-results/claude-code--pro
  ject-analysis--terminalcp-cli--20250816001349939001-prompt.md and follow 
  the instructions.

⏺ I'll read the file and follow the instructions it contains.

⏺ Read(evaluation-results/claude-code--project-analysis--terminalcp-cli--20
      250816001349939001-prompt.md)
  ⎿  Read 71 lines (ctrl+r to expand)

⏺ I'll follow the instructions to complete this task using the Terminalcp
  CLI tool. Let me start by starting opencode with the specified model.

⏺ Bash(npx tsx src/index.ts start opencode opencode --model
      anthropic/claude-sonnet-4-20250514)
  ⎿  Started session: opencode

⏺ Now let me check the current state to see if opencode has started
  properly:

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿                        █▀▀█ █▀▀█ █▀▀ █▀▀▄ █▀▀ █▀▀█ █▀▀▄ █▀▀

                           █░░█ █░░█ █▀▀ █░░█ █░░ █░░█ █░░█ █▀▀
     … +39 lines (ctrl+r to expand)

⏺ Good! Opencode has started successfully. Now I need to use the /models
  command to switch to GPT OSS 120B:

⏺ Bash(npx tsx src/index.ts stdin opencode "/models" ::Enter)
  ⎿  (No content)

⏺ Let me check the output to see if the models dialog appeared:

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿             ┃                                                       ┃

                ┃   Select Model                                  esc   ┃
     … +39 lines (ctrl+r to expand)

⏺ Perfect! The models dialog is open and I can see "GPT OSS 120B
  OpenRouter" in the list. Now I need to type "GPT OSS 120B" to filter the
  list and then select it:

⏺ Bash(npx tsx src/index.ts stdin opencode "GPT OSS 120B")
  ⎿  (No content)

⏺ Let me check the current state:

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿             ┃                                                       ┃

                ┃   Select Model                                  esc   ┃
     … +39 lines (ctrl+r to expand)

⏺ Great! The filter is working and I can see "GPT OSS 120B OpenRouter" in
  the list. Now I need to press Enter to select it:

  Bash(npx tsx src/index.ts stdin opencode ::Enter)
  ⎿  (No content)

⏺ Let me check if the model has been switched successfully:

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿                        █▀▀█ █▀▀█ █▀▀ █▀▀▄ █▀▀ █▀▀█ █▀▀▄ █▀▀

                           █░░█ █░░█ █▀▀ █░░█ █░░ █░░█ █░░█ █▀▀
     … +39 lines (ctrl+r to expand)

⏺ Excellent! The model has been successfully switched to "Groq GPT OSS
  120B" as shown in the bottom right corner. Now I need to ask it to
  analyze the project by reading the README.md:

  Bash(npx tsx src/index.ts stdin opencode "Read README.md explain what
      this project does" ::Enter)
  ⎿  (No content)

⏺ Let me check the response:

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    13.2K/10% ($0
    … +43 lines (ctrl+r to expand)


⏺ I can see that GPT OSS 120B is currently processing the request (showing
  "ing..." at the bottom). Let me wait a moment and check again to get the
  complete response:

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ I can see the response is complete now. Let me capture the full response
  by getting more lines from the scrollback to ensure I have the complete
  analysis:

  Bash(npx tsx src/index.ts stdout opencode 100)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ I can see this is only showing the end of the response. Let me try to
  scroll up to get the complete response by getting more lines:

  Bash(npx tsx src/index.ts stdout opencode 1000)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ I notice the response seems to be truncated. Let me try using PageUp to
  scroll up and see the full response:

  Bash(npx tsx src/index.ts stdin opencode ::PageUp ::PageUp ::PageUp)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Good! I'm getting more of the response. Let me continue scrolling up to
  get the beginning:

  Bash(npx tsx src/index.ts stdin opencode ::PageUp ::PageUp ::PageUp
      ::PageUp ::PageUp)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Great! Now I can see the beginning of the response. Let me scroll down
  through the complete response to capture it all. Let me use PageDown to
  go through the entire response:

  Bash(npx tsx src/index.ts stdin opencode ::PageDown)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


  Bash(npx tsx src/index.ts stdin opencode ::PageDown)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


  Bash(npx tsx src/index.ts stdin opencode ::PageDown)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


  Bash(npx tsx src/index.ts stdin opencode ::PageDown)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


  Bash(npx tsx src/index.ts stdin opencode ::PageDown)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


  Bash(npx tsx src/index.ts stdin opencode ::PageDown)
  ⎿  (No content)

  Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Perfect! Now I have captured the complete response. Let me stop the
  opencode session to clean up:

  Bash(npx tsx src/index.ts stop opencode)
  ⎿  stopped opencode

⏺ TASK_COMPLETE

  I successfully completed the task. Here is the complete response from GPT
   OSS 120B analyzing the project:

  GPT OSS 120B's Complete Analysis of the terminalcp Project:

  Project Overview – terminalcp

  terminalcp is a Node.js library and CLI that lets AI agents (or any
  program) control interactive command-line tools just like a human would.
  It provides a "Playwright-for-the-terminal" style interface where
  processes are started in a pseudo-TTY, and the agent can send keystrokes,
   read output, and keep sessions alive.

  Core Capabilities

  • Spawn & control any CLI (debuggers, REPLs, build tools, etc.) in
  real-time.
  • Two output modes:
  - Terminal mode (stdout) – full rendered screen (good for TUIs,
  debuggers).
  - Stream mode – raw incremental output (good for logs, builds).
  • Full PTY emulation (colors, cursor movement, special keys) via node-pty
   + headless xterm.js.
  • Multiple concurrent sessions that persist across client disconnects.
  • MCP server exposing a single JSON-based tool (terminalcp) for AI-driven
   interaction.
  • CLI (terminalcp command) that mirrors the MCP functionality (start,
  stop, send input, get output, attach, etc.).
  • Attachable sessions – users can attach to AI-spawned processes from
  their own terminal (like screen/tmux).

  Architecture

  1. TerminalManager – core library handling PTY creation, I/O, and
  terminal emulation.
  2. TerminalServer – background process listening on a Unix-socket,
  managing all sessions.
  3. TerminalClient – used by both the MCP server and CLI to talk to the
  server.
  4. User Interfaces – MCP server (for AI agents) and CLI (for humans) both
   use the same underlying API.

  Typical Use-Cases

  • Debugging (LLDB, GDB, pdb) – step-through code, get backtraces, etc.
  • Running other AI tools (Claude Code, Gemini CLI) as subprocesses.
  • Driving REPLs, database shells, system monitors.
  • Testing/automating TUIs (vim, htop) via programmatic API.
  • Monitoring long-running processes (build logs, server output) with
  incremental streaming.

  How to Use

  • MCP: send JSON actions (start, stdin, stdout, stream, stop, etc.) to
  the terminalcp tool.
  • CLI: terminalcp start  "", terminalcp stdin  "cmd" ::Enter, terminalcp
  stdout , terminalcp attach , etc.
  • Programmatic: import TerminalManager in TypeScript/JavaScript and use
  its methods (start, sendInput, stdout, stream, stop).

  Development

  • Install with Node 20+, run npm install, npm test, npm run build.
  • The server persists sessions in ~/.terminalcp/server.socket.
  • Sessions can be listed, stopped, or killed via the MCP or CLI.

  In short: terminalcp provides a robust, programmatic way for AI agents
  (or any code) to spawn, control, and monitor interactive terminal
  applications, with full PTY support, persistence, and both MCP and CLI
  interfaces.

> /cost 
  ⎿ Total cost:            $0.84
    Total duration (API):  2m 43.8s
    Total duration (wall): 2m 34.2s
    Total code changes:    0 lines added, 0 lines removed
    Usage by model:
        claude-3-5-haiku:  48.0k input, 1.4k output, 0 cache read, 0 cache 
    write
           claude-sonnet:  388 input, 4.4k output, 1.8m cache read, 50.0k 
    cache write

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